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Google Keyword Rankings for : category learning by inference and classification
1
Category Learning by Inference and Classification
https://www.sciencedirect.com/science/article/abs/pii/S0749596X98925669
In Classification Learning, subjects learned categories by predicting the class ...
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https://www.sciencedirect.com/science/article/abs/pii/S0749596X98925669
In Classification Learning, subjects learned categories by predicting the class ...
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2
Category learning by inference and classification. - APA PsycNet
https://psycnet.apa.org/record/1998-04837-007
To explore this idea, the authors investigated how 3 different methods of category learning—classification learning, inference learning, and mixed learning ...
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https://psycnet.apa.org/record/1998-04837-007
To explore this idea, the authors investigated how 3 different methods of category learning—classification learning, inference learning, and mixed learning ...
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3
Comparing methods of category learning: Classification ...
https://link.springer.com/article/10.3758/s13421-020-01022-8
Correspondingly, categories can be learned in two distinct ways, by classification and feature inference.
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https://link.springer.com/article/10.3758/s13421-020-01022-8
Correspondingly, categories can be learned in two distinct ways, by classification and feature inference.
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4
(PDF) Category Learning by Inference and Classification
https://www.researchgate.net/publication/257255668_Category_Learning_by_Inference_and_Classification
In Inference Learning, subjects learned categories by predicting a feature value of a stimulus given the class to which it belonged and information about its ...
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https://www.researchgate.net/publication/257255668_Category_Learning_by_Inference_and_Classification
In Inference Learning, subjects learned categories by predicting a feature value of a stimulus given the class to which it belonged and information about its ...
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5
Diagnosticity in Category Learning ... - Taylor & Francis eBooks
https://www.taylorfrancis.com/chapters/edit/10.4324/9781315782379-68/diagnosticity-category-learning-classification-inference-seth-chin-parker-brian-ross
Categories are learned in many ways, but the focus of much category learning research has been on classification learning. In classification learning, the.
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https://www.taylorfrancis.com/chapters/edit/10.4324/9781315782379-68/diagnosticity-category-learning-classification-inference-seth-chin-parker-brian-ross
Categories are learned in many ways, but the focus of much category learning research has been on classification learning. In classification learning, the.
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6
[PDF] Category Learning by Inference and Classification | Semantic ...
https://www.semanticscholar.org/paper/Category-Learning-by-Inference-and-Classification-Yamauchi-Markman/a5cd739a4eb99cc84316ab43ab5c06b3a4c0f0bf
This work compared feature inference learning of category structures from Shepard, Hovland, and Jenkins with classification learning and found differences ...
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https://www.semanticscholar.org/paper/Category-Learning-by-Inference-and-Classification-Yamauchi-Markman/a5cd739a4eb99cc84316ab43ab5c06b3a4c0f0bf
This work compared feature inference learning of category structures from Shepard, Hovland, and Jenkins with classification learning and found differences ...
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7
Classification versus feature inference - PubMed
https://pubmed.ncbi.nlm.nih.gov/32078736/
Categories have at least two main functions: classification of instances and feature inference. Classification involves assigning an instance to a category, ...
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https://pubmed.ncbi.nlm.nih.gov/32078736/
Categories have at least two main functions: classification of instances and feature inference. Classification involves assigning an instance to a category, ...
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8
Classification and Inference in Category Learning
https://journal.psych.ac.cn/xlkxjz/EN/abstract/abstract1255.shtml
Classification is a kind of inductive inference and its learners are highly sensitivity to diagnostic features between categories and possibility to learn ...
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https://journal.psych.ac.cn/xlkxjz/EN/abstract/abstract1255.shtml
Classification is a kind of inductive inference and its learners are highly sensitivity to diagnostic features between categories and possibility to learn ...
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9
Diagnosticity and Prototypicality in Category Learning ... - ERIC
https://eric.ed.gov/?id=EJ689138
Classification learners were highly sensitive to diagnostic features but not sensitive to nondiagnostic, but prototypical, features. Inference learners were ...
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https://eric.ed.gov/?id=EJ689138
Classification learners were highly sensitive to diagnostic features but not sensitive to nondiagnostic, but prototypical, features. Inference learners were ...
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10
Classification versus inference learning - ProQuest
https://www.proquest.com/scholarly-journals/classification-versus-inference-learning/docview/920257074/se-2
Categories underlie a variety of cognitive tasks, including problem solving, classification, prediction, explanations, and inferences. Knowing the category an ...
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https://www.proquest.com/scholarly-journals/classification-versus-inference-learning/docview/920257074/se-2
Categories underlie a variety of cognitive tasks, including problem solving, classification, prediction, explanations, and inferences. Knowing the category an ...
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11
classification versus inference learning contrasted with real ...
https://core.ac.uk/download/pdf/4824729.pdf
learning, which reflect the goals of the tasks. Inference learners focus more on what each category is like, while classification learners focus on finding ...
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https://core.ac.uk/download/pdf/4824729.pdf
learning, which reflect the goals of the tasks. Inference learners focus more on what each category is like, while classification learners focus on finding ...
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12
Category Learning and Inference - Thinking and Reasoning
https://www.mitchmedical.us/thinking-reasoning/category-learning-and-inference.html
According to this theory, categorization depends on similarity to the prototypes. For example, to decide whether some animal is a bird or a ...
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https://www.mitchmedical.us/thinking-reasoning/category-learning-and-inference.html
According to this theory, categorization depends on similarity to the prototypes. For example, to decide whether some animal is a bird or a ...
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13
A MODEL OF CATEGORY LEARNING SUSTAIN
http://groups.psych.northwestern.edu/medin/publications/Love,%20Medin,%20Gureckis%202004%20sustain.pdf
of inference learning, unsupervised learning, category construction, and contexts where identification learning is faster than classification learning.
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http://groups.psych.northwestern.edu/medin/publications/Love,%20Medin,%20Gureckis%202004%20sustain.pdf
of inference learning, unsupervised learning, category construction, and contexts where identification learning is faster than classification learning.
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14
Diagnosticity in Category Learning by ... - eScholarship
https://escholarship.org/uc/item/2h09n0hv
Diagnosticity in Category Learning by Classification and Inference ... For improved accessibility of PDF content, download the file to your device. Thumbnails
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https://escholarship.org/uc/item/2h09n0hv
Diagnosticity in Category Learning by Classification and Inference ... For improved accessibility of PDF content, download the file to your device. Thumbnails
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15
Modeling Classification and Inference Learning
https://www.aaai.org/Papers/AAAI/2000/AAAI00-021.pdf
which learning mode is engaged. Inference learn- ing tends to focus subjects on the internal struc- ture of each category, while classification learning.
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https://www.aaai.org/Papers/AAAI/2000/AAAI00-021.pdf
which learning mode is engaged. Inference learn- ing tends to focus subjects on the internal struc- ture of each category, while classification learning.
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16
Effects of Classification and Inference Training on Category ...
https://cpb-us-w2.wpmucdn.com/u.osu.edu/dist/1/56827/files/2018/06/Deng-Sloutsky-2015-2a8mo71.pdf
may result in different representations of the same category. First, in order for classification and inference learning to be equivalent.
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https://cpb-us-w2.wpmucdn.com/u.osu.edu/dist/1/56827/files/2018/06/Deng-Sloutsky-2015-2a8mo71.pdf
may result in different representations of the same category. First, in order for classification and inference learning to be equivalent.
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17
Learning and Retention Through Predictive Inference and ...
http://bradlove.org/papers/SakamotoLove2010.pdf
in category learning to learning tasks situated in an educational context. In Experiment 1, learning through predictive inference and classification were ...
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http://bradlove.org/papers/SakamotoLove2010.pdf
in category learning to learning tasks situated in an educational context. In Experiment 1, learning through predictive inference and classification were ...
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18
Learning about the Internal Structure of ... - SAGE Journals
https://journals.sagepub.com/doi/10.1080/17470218.2013.871567
One possibility is that inference learners will outperform classification learners on these novel measures of within-category knowledge, even when feature ...
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https://journals.sagepub.com/doi/10.1080/17470218.2013.871567
One possibility is that inference learners will outperform classification learners on these novel measures of within-category knowledge, even when feature ...
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19
Learning about the internal structure of categories through ...
https://www.tandfonline.com/doi/abs/10.1080/17470218.2013.871567
Although inference learning promoted representations that included a broad range of category-typical features, classification learning promoted greater ...
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https://www.tandfonline.com/doi/abs/10.1080/17470218.2013.871567
Although inference learning promoted representations that included a broad range of category-typical features, classification learning promoted greater ...
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20
Categorization - Wikipedia
https://en.wikipedia.org/wiki/Categorization
Category learningEdit · Rule-based tasks present categories that participants can learn through explicit reasoning processes. · Information-integration tasks ...
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https://en.wikipedia.org/wiki/Categorization
Category learningEdit · Rule-based tasks present categories that participants can learn through explicit reasoning processes. · Information-integration tasks ...
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21
Feature inference learning and eyetracking
https://s18798.pcdn.co/bobrehderlab/wp-content/uploads/sites/20443/2021/01/Rehder-et-al.-09-JML.pdf
Besides traditional supervised classification learning, people can learn categories by infer- ring the missing features of category members.
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https://s18798.pcdn.co/bobrehderlab/wp-content/uploads/sites/20443/2021/01/Rehder-et-al.-09-JML.pdf
Besides traditional supervised classification learning, people can learn categories by infer- ring the missing features of category members.
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22
A comparison o" by Seth Chin-Parker and Brian H. Ross
https://digitalcommons.denison.edu/facultypubs/273/
Chin-Parker, S., & Ross, B. H. (2004). Diagnosticity and Prototypicality in Category Learning: A Comparison of Inference Learning and Classification Learning.
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https://digitalcommons.denison.edu/facultypubs/273/
Chin-Parker, S., & Ross, B. H. (2004). Diagnosticity and Prototypicality in Category Learning: A Comparison of Inference Learning and Classification Learning.
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23
A difficulty predictor for perceptual category learning | JOV
https://jov.arvojournals.org/article.aspx?articleid=2737099
Predicting human performance in perceptual categorization tasks in which category membership is determined by similarity has been historically difficult.
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https://jov.arvojournals.org/article.aspx?articleid=2737099
Predicting human performance in perceptual categorization tasks in which category membership is determined by similarity has been historically difficult.
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24
How Category Labels Influence Feature Inference
https://onlinelibrary.wiley.com/doi/pdf/10.1111/cogs.12206
Two main uses of categories are classification and feature inference, ... representation to category learning data in Johansen & Kruschke, 2005; Yamauchi &.
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https://onlinelibrary.wiley.com/doi/pdf/10.1111/cogs.12206
Two main uses of categories are classification and feature inference, ... representation to category learning data in Johansen & Kruschke, 2005; Yamauchi &.
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25
Alternative Algorithms for Category Learning
https://cocosci.princeton.edu/tom/papers/rationalapproximations.pdf
In the second part of the article, we apply the rational approximation idea to categorization problems, using Anderson's (1990, 1991) ratio- nal model. We first ...
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https://cocosci.princeton.edu/tom/papers/rationalapproximations.pdf
In the second part of the article, we apply the rational approximation idea to categorization problems, using Anderson's (1990, 1991) ratio- nal model. We first ...
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26
(PDF) Attentional and Representational Flexibility of Feature ...
https://www.academia.edu/58178090/Attentional_and_Representational_Flexibility_of_Feature_Inference_Learning
... inference learning may motivate learners to acquire more within-category and prototypical information compared to standard supervised classification.
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https://www.academia.edu/58178090/Attentional_and_Representational_Flexibility_of_Feature_Inference_Learning
... inference learning may motivate learners to acquire more within-category and prototypical information compared to standard supervised classification.
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27
Acta Psychologica Sinica, Vol. 41 No. 1 , Pages 44 -52
http://www.fed.cuhk.edu.hk/ceric/aps/200900410001/0044.htm
In this paper, we compare classification learning with another mean of learning categories: inference learning. In inference task, participants predict the ...
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http://www.fed.cuhk.edu.hk/ceric/aps/200900410001/0044.htm
In this paper, we compare classification learning with another mean of learning categories: inference learning. In inference task, participants predict the ...
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28
Learning to learn categories
https://psychologicalsciences.unimelb.edu.au/__data/assets/pdf_file/0012/2578278/PerforsTenenbaum2009.pdf
levels of abstraction: learning about kinds of categories and making inferences about what categories are like in general.
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https://psychologicalsciences.unimelb.edu.au/__data/assets/pdf_file/0012/2578278/PerforsTenenbaum2009.pdf
levels of abstraction: learning about kinds of categories and making inferences about what categories are like in general.
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29
Feature-to-Feature Inference Under Conditions of Cue ...
https://scholarlypublishingcollective.org/uip/ajp/article/130/1/35/258174/Feature-to-Feature-Inference-Under-Conditions-of
Inference and classification learning of abstract coherent categories . Journal of Experimental Psychology: Learning, Memory, and Cognition.
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https://scholarlypublishingcollective.org/uip/ajp/article/130/1/35/258174/Feature-to-Feature-Inference-Under-Conditions-of
Inference and classification learning of abstract coherent categories . Journal of Experimental Psychology: Learning, Memory, and Cognition.
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30
Feature Inference Under Conditions of Cue Restriction ... - jstor
https://www.jstor.org/stable/10.5406/amerjpsyc.130.1.0035
although the dimension to category label correlation matched that of the correlated condition. ... that classification and inference learning lead to dif-.
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https://www.jstor.org/stable/10.5406/amerjpsyc.130.1.0035
although the dimension to category label correlation matched that of the correlated condition. ... that classification and inference learning lead to dif-.
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31
Premise typicality as feature inference decision-making in ...
https://europepmc.org/article/pmc/pmc9018646
Making property inferences for category instances is important and has been studied in two largely separate areas-categorical induction and perceptual ...
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https://europepmc.org/article/pmc/pmc9018646
Making property inferences for category instances is important and has been studied in two largely separate areas-categorical induction and perceptual ...
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32
Predicting classes with classification | Machine Learning in the ...
https://www.elastic.co/guide/en/machine-learning/current/ml-dfa-classification.html
The class_probability is a value between 0 and 1, which indicates how likely it is that a given data point belongs to a certain class. The higher the number, ...
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https://www.elastic.co/guide/en/machine-learning/current/ml-dfa-classification.html
The class_probability is a value between 0 and 1, which indicates how likely it is that a given data point belongs to a certain class. The higher the number, ...
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33
Robert M. Nosofsky's home page
https://nosofsky.cogs.indiana.edu/
Robert Nosofsky s primary research is in the area of computational modeling of human category learning and representation, and relations between categorization ...
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https://nosofsky.cogs.indiana.edu/
Robert Nosofsky s primary research is in the area of computational modeling of human category learning and representation, and relations between categorization ...
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34
Visual category learning - CATLAB
http://catlab.psy.vanderbilt.edu/wp-content/uploads/RP-Wires2013.pdf
While it is common to test categorization performance using natural, real-world categories of objects,41 when testing category learning it far more.
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http://catlab.psy.vanderbilt.edu/wp-content/uploads/RP-Wires2013.pdf
While it is common to test categorization performance using natural, real-world categories of objects,41 when testing category learning it far more.
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35
Development of Attention and Accuracy in Learning ... - Frontiers
https://www.frontiersin.org/articles/10.3389/fpsyg.2021.544135/full
Another is that objects are categorized based on their similarity to other members of the category or to a prototype. For example, if an animal ...
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https://www.frontiersin.org/articles/10.3389/fpsyg.2021.544135/full
Another is that objects are categorized based on their similarity to other members of the category or to a prototype. For example, if an animal ...
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36
Perceptual and Conceptual Cues in Classification and ...
http://psych.colorado.edu/~colunga/publications/Sims+Colunga-CogSci11.pdf
Perceptual and Conceptual Cues in Classification and Inference Tasks ... information to several types of category learning and use.
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http://psych.colorado.edu/~colunga/publications/Sims+Colunga-CogSci11.pdf
Perceptual and Conceptual Cues in Classification and Inference Tasks ... information to several types of category learning and use.
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37
Putting category learning in order - PCL
https://pcl.sitehost.iu.edu/papers/blockedinterleaved.pdf
Participants had to classify each stimulus in one of the two categories with corrective feedback. The results showed that participants were better at learning ...
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https://pcl.sitehost.iu.edu/papers/blockedinterleaved.pdf
Participants had to classify each stimulus in one of the two categories with corrective feedback. The results showed that participants were better at learning ...
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38
References in: A new theory of classification and feature ...
https://philarchive.org/references/COLANT-3
A new theory of classification and feature inference learning: An exemplar ... A Neuropsychological Theory of Multiple Systems in Category Learning.
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https://philarchive.org/references/COLANT-3
A new theory of classification and feature inference learning: An exemplar ... A Neuropsychological Theory of Multiple Systems in Category Learning.
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39
Bayesian Approaches to Color Category Learning
http://imbs.uci.edu/~kjameson/ECST/Griffiths_BayesianApproachesToColorCategoryLearning.pdf
Bayesian approaches to color category learning formalize learning as a problem of Bayesian inference, requiring the learner to form generalizations that go ...
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http://imbs.uci.edu/~kjameson/ECST/Griffiths_BayesianApproachesToColorCategoryLearning.pdf
Bayesian approaches to color category learning formalize learning as a problem of Bayesian inference, requiring the learner to form generalizations that go ...
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40
Cluster-Based Inference for Memory-Based Cognition - bioRxiv
https://www.biorxiv.org/content/10.1101/2022.04.22.489185v1.full
The RCM is a classic model of category learning from the behavioural psychology literature which has been revisited in light of developments in ...
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https://www.biorxiv.org/content/10.1101/2022.04.22.489185v1.full
The RCM is a classic model of category learning from the behavioural psychology literature which has been revisited in light of developments in ...
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41
Machine Learning Glossary - Google Developers
https://developers.google.com/machine-learning/glossary
classification model. #fundamentals. A model whose prediction is a class. For example, the following are all classification models:.
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https://developers.google.com/machine-learning/glossary
classification model. #fundamentals. A model whose prediction is a class. For example, the following are all classification models:.
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42
Categorization - IResearchNet - What is Psychology?
https://psychology.iresearchnet.com/developmental-psychology/cognitive-development/categorization/
Objects in the same category are likely to share certain attributes, and category membership allows inferences to be drawn. The term category refers to a ...
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https://psychology.iresearchnet.com/developmental-psychology/cognitive-development/categorization/
Objects in the same category are likely to share certain attributes, and category membership allows inferences to be drawn. The term category refers to a ...
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43
A New Theory of Classification and Feature Inference Learning
https://www.slideshare.net/bobcolner/a-new-theory-of-classification-and-feature-inference-learning-an-exemplar-fragment-model
A new model of human category learning is presented. Novel use of eye-tracking data to directly estimate model parameters.
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https://www.slideshare.net/bobcolner/a-new-theory-of-classification-and-feature-inference-learning-an-exemplar-fragment-model
A new model of human category learning is presented. Novel use of eye-tracking data to directly estimate model parameters.
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44
Learning a complex category structure by classification and ...
https://curve.carleton.ca/5c142562-7f0a-4afc-8531-a3616cfce638
Learning a complex category structure by classification and feature inference ; Creator: Howell, Glen ; Date: 2009 ; Subject: Cognitive psychology. Psychology, ...
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https://curve.carleton.ca/5c142562-7f0a-4afc-8531-a3616cfce638
Learning a complex category structure by classification and feature inference ; Creator: Howell, Glen ; Date: 2009 ; Subject: Cognitive psychology. Psychology, ...
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45
Category acquisition in children: comparing learning through ...
https://researchers.mq.edu.au/en/publications/category-acquisition-in-children-comparing-learning-through-class
Category acquisition in children: comparing learning through classification and inference ; English · 74-74 · 1 · Australian Journal of Psychology · 57.
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https://researchers.mq.edu.au/en/publications/category-acquisition-in-children-comparing-learning-through-class
Category acquisition in children: comparing learning through classification and inference ; English · 74-74 · 1 · Australian Journal of Psychology · 57.
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46
Learning nonlinearly separable categories by inference and ...
https://www.ucl.ac.uk/pals/research/experimental-psychology/publication/learning-nonlinearly-separable-categories-by-inference-and-classification/
Learning nonlinearly separable categories by inference and classification. · Publication details · Contact us: · Part of:.
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https://www.ucl.ac.uk/pals/research/experimental-psychology/publication/learning-nonlinearly-separable-categories-by-inference-and-classification/
Learning nonlinearly separable categories by inference and classification. · Publication details · Contact us: · Part of:.
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47
17. Classification - Computational and Inferential Thinking
https://inferentialthinking.com/chapters/17/Classification.html
Machine learning is a class of techniques for automatically finding patterns in data and using it to draw inferences or make predictions.
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https://inferentialthinking.com/chapters/17/Classification.html
Machine learning is a class of techniques for automatically finding patterns in data and using it to draw inferences or make predictions.
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48
Classification and Categorization | Boundless Psychology
https://www.coursehero.com/study-guides/boundless-psychology/classification-and-categorization/
Prototype theory: Under prototype theory, all treelike things will be judged based on an individual's prototype of a tree. The middle category TREE is more ...
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https://www.coursehero.com/study-guides/boundless-psychology/classification-and-categorization/
Prototype theory: Under prototype theory, all treelike things will be judged based on an individual's prototype of a tree. The middle category TREE is more ...
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49
Word Learning as Category Formation
https://scholarworks.umass.edu/cgi/viewcontent.cgi?article=1017&context=scil
A fundamental question in word learning is ... able to generalize the total class (Smith, 1979; ... counted for on a Bayesian inference theory (Xu and.
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https://scholarworks.umass.edu/cgi/viewcontent.cgi?article=1017&context=scil
A fundamental question in word learning is ... able to generalize the total class (Smith, 1979; ... counted for on a Bayesian inference theory (Xu and.
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50
Exemplar-based inference in multi-attribute decision making
https://journal.sjdm.org/bn5/bn5.html
Exemplar models have proven particularly successful for describing categorization learning and categorical decisions (Nosofsky & Johansen, 2000; cf. Medin & ...
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https://journal.sjdm.org/bn5/bn5.html
Exemplar models have proven particularly successful for describing categorization learning and categorical decisions (Nosofsky & Johansen, 2000; cf. Medin & ...
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51
Effects of classification and inference training on category ...
https://repository.um.edu.mo/handle/10692/20439
The current study attempted to answer these questions by examining category learning and category representation.
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https://repository.um.edu.mo/handle/10692/20439
The current study attempted to answer these questions by examining category learning and category representation.
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52
The What and Why of Categories – The Discipline of Organizing
https://berkeley.pressbooks.pub/tdo4p/chapter/the-what-and-why-of-categories/
Most psychologists argue that category learning starts with general learning mechanisms that are very perceptually based, but they do not agree whether to ...
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https://berkeley.pressbooks.pub/tdo4p/chapter/the-what-and-why-of-categories/
Most psychologists argue that category learning starts with general learning mechanisms that are very perceptually based, but they do not agree whether to ...
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53
An Inference Approach to Basic Level of Categorization
https://dl.acm.org/doi/10.1145/2806416.2806533
References · L. W. Barsalou. Ideals, central tendency, and frequency of instantiation as determinants of graded structure in categories. · D. M. Blei, A. Y. Ng, ...
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https://dl.acm.org/doi/10.1145/2806416.2806533
References · L. W. Barsalou. Ideals, central tendency, and frequency of instantiation as determinants of graded structure in categories. · D. M. Blei, A. Y. Ng, ...
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54
GRAPH INFERENCE LEARNING FOR SEMI-SUPERVISED ...
https://openreview.net/pdf?id=r1evOhEKvH
In this work, we address semi-supervised classification of graph data, where the categories of those unlabeled nodes are inferred from labeled nodes as well ...
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https://openreview.net/pdf?id=r1evOhEKvH
In this work, we address semi-supervised classification of graph data, where the categories of those unlabeled nodes are inferred from labeled nodes as well ...
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55
Machine learning for causal inference - Cross Validated
https://stats.stackexchange.com/questions/565090/machine-learning-for-causal-inference
I have a multiclass classification problem where the target variable is actually different categories of causes ...
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https://stats.stackexchange.com/questions/565090/machine-learning-for-causal-inference
I have a multiclass classification problem where the target variable is actually different categories of causes ...
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56
Joint Hierarchical Category Structure Learning and Large ...
https://arxiv.org/pdf/1709.05072
image classification method based on learning hierarchical inter- class structures. ... and multi-class classification inference.
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https://arxiv.org/pdf/1709.05072
image classification method based on learning hierarchical inter- class structures. ... and multi-class classification inference.
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57
An Inference Approach to Basic Level of ... - Microsoft
https://www.microsoft.com/en-us/research/wp-content/uploads/2016/02/scoring.pdf
Humans understand the world by classifying objects into concepts. The concepts an object belongs to form a set of hierarchically organized categories ...
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https://www.microsoft.com/en-us/research/wp-content/uploads/2016/02/scoring.pdf
Humans understand the world by classifying objects into concepts. The concepts an object belongs to form a set of hierarchically organized categories ...
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58
Transfer learning for TensorFlow text classification models in ...
https://aws.amazon.com/blogs/machine-learning/transfer-learning-for-tensorflow-text-classification-models-in-amazon-sagemaker/
According to the number of class labels in the training data, a classification layer is attached to the pre-trained TensorFlow hub model. The ...
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https://aws.amazon.com/blogs/machine-learning/transfer-learning-for-tensorflow-text-classification-models-in-amazon-sagemaker/
According to the number of class labels in the training data, a classification layer is attached to the pre-trained TensorFlow hub model. The ...
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59
A Novel Role for the Hippocampus in Category Learning
https://www.jneurosci.org/content/38/31/6803
One such type of generalization, episodic inference, allows memory of past and current events to be combined so that one can make inferences ...
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https://www.jneurosci.org/content/38/31/6803
One such type of generalization, episodic inference, allows memory of past and current events to be combined so that one can make inferences ...
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60
Tracking prototype and exemplar representations in the brain ...
https://elifesciences.org/articles/59360
Thus, the categorization gradient driven by higher accuracy for items closer to category prototypes observed during learning was also strong ...
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https://elifesciences.org/articles/59360
Thus, the categorization gradient driven by higher accuracy for items closer to category prototypes observed during learning was also strong ...
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61
14 Different Types of Learning in Machine Learning
https://machinelearningmastery.com/types-of-learning-in-machine-learning/
There are two main types of supervised learning problems: they are classification that involves predicting a class label and regression that ...
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https://machinelearningmastery.com/types-of-learning-in-machine-learning/
There are two main types of supervised learning problems: they are classification that involves predicting a class label and regression that ...
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62
Reprints - Brian Ross
https://prod2020.psychology.illinois.edu/reprints/index.php?page=request_article&site_id=19&article_id=278
Chin-Parker, S., & Ross, B.H. (2004). Diagnosticity and prototypicality in category learning: A comparison of inference learning and ...
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https://prod2020.psychology.illinois.edu/reprints/index.php?page=request_article&site_id=19&article_id=278
Chin-Parker, S., & Ross, B.H. (2004). Diagnosticity and prototypicality in category learning: A comparison of inference learning and ...
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63
Categorization and Concept Learning - Form and Format of ...
https://education.stateuniversity.com/pages/1816/Categorization-Concept-Learning.html
Educators should judiciously use definitions to teach new concepts. Students will not typically use definitions to judge category membership. Exposing students ...
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https://education.stateuniversity.com/pages/1816/Categorization-Concept-Learning.html
Educators should judiciously use definitions to teach new concepts. Students will not typically use definitions to judge category membership. Exposing students ...
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64
From Conditioning to Category Learning: An Adaptive ...
https://www.gluck.edu/pdf/GluckBower1988.pdf
logistic regression and to a Bayesian inference model (see ... models of subjects' learning to classify stimuli into categories.
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https://www.gluck.edu/pdf/GluckBower1988.pdf
logistic regression and to a Bayesian inference model (see ... models of subjects' learning to classify stimuli into categories.
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65
A Neuropsychological Theory of Multiple Systems in Category ...
http://www.ebire.org/aphasia/turken/a_neuropsychological_multiple.pdf
We believe that standard perceptual categorization in- volves a similar procedural learning process. For example, parti- cipants in the Maddox and Ashby (1993) ...
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http://www.ebire.org/aphasia/turken/a_neuropsychological_multiple.pdf
We believe that standard perceptual categorization in- volves a similar procedural learning process. For example, parti- cipants in the Maddox and Ashby (1993) ...
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66
Selective sampling and inductive inference - Danielle Navarro
https://djnavarro.net/papers/2019_samplingframes.pdf
This contrasts with work in fields such as statistics, machine learning, ... problem with a prior distribution P(h) defined over some class of possible ...
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https://djnavarro.net/papers/2019_samplingframes.pdf
This contrasts with work in fields such as statistics, machine learning, ... problem with a prior distribution P(h) defined over some class of possible ...
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67
Models of visual categorization - Serre Lab
https://serre-lab.clps.brown.edu/wp-content/uploads/2018/03/serre2016.pdf
to make inferences regarding an object's properties ... After learning, the algorithm tries to predict the category label of a new stimulus x* by ...
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https://serre-lab.clps.brown.edu/wp-content/uploads/2018/03/serre2016.pdf
to make inferences regarding an object's properties ... After learning, the algorithm tries to predict the category label of a new stimulus x* by ...
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68
Literature Review on Mental Models and Linear Separability
https://apps.dtic.mil/sti/pdfs/ADA585732.pdf
This concept comes from the domain of category learning; the extent to which humans ... categories could be learned through classification and inference.
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https://apps.dtic.mil/sti/pdfs/ADA585732.pdf
This concept comes from the domain of category learning; the extent to which humans ... categories could be learned through classification and inference.
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69
Are open set classification methods effective on large-scale ...
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0238302
In classification with a reject option, the test distribution has the same categories as the training distribution; however, a classifier should ...
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https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0238302
In classification with a reject option, the test distribution has the same categories as the training distribution; however, a classifier should ...
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70
Inference and coherence in causal-based artifact categorization
https://guillermopuebla.github.io/assets/pdf/inference_coherence_manuscript.pdf
exemplars where category relevant properties are unknown. Regarding the issue of differences in causal categorization between artifacts.
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https://guillermopuebla.github.io/assets/pdf/inference_coherence_manuscript.pdf
exemplars where category relevant properties are unknown. Regarding the issue of differences in causal categorization between artifacts.
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71
Audio Deep Learning Made Simple: Sound Classification ...
https://towardsdatascience.com/audio-deep-learning-made-simple-sound-classification-step-by-step-cebc936bbe5
It involves learning to classify sounds and to predict the category of that sound. This type of problem can be applied to many practical ...
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https://towardsdatascience.com/audio-deep-learning-made-simple-sound-classification-step-by-step-cebc936bbe5
It involves learning to classify sounds and to predict the category of that sound. This type of problem can be applied to many practical ...
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72
Proceedings of the Twenty-fourth Annual Conference of the ...
https://books.google.com/books?id=lU6fDwAAQBAJ&pg=PA183&lpg=PA183&dq=category+learning+by+inference+and+classification&source=bl&ots=9dg3KqtpNg&sig=ACfU3U0LVPPSrsb3Ko6oH8d3PJklfHoT-Q&hl=en&sa=X&ved=2ahUKEwjX0r-p2t37AhUZhIkEHSiaBw8Q6AF6BQjNAhAD
To understand category learning as it exists outside of the laboratory, ... as to why classification and inference learning lead to such different category ...
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https://books.google.com/books?id=lU6fDwAAQBAJ&pg=PA183&lpg=PA183&dq=category+learning+by+inference+and+classification&source=bl&ots=9dg3KqtpNg&sig=ACfU3U0LVPPSrsb3Ko6oH8d3PJklfHoT-Q&hl=en&sa=X&ved=2ahUKEwjX0r-p2t37AhUZhIkEHSiaBw8Q6AF6BQjNAhAD
To understand category learning as it exists outside of the laboratory, ... as to why classification and inference learning lead to such different category ...
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73
Essentialism as a Generative Theory of Classification
https://academic.oup.com/book/36085/chapter/313206091
Although unobservable, essential features can nonetheless affect classification by changing the evidence that observable features provide for category ...
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https://academic.oup.com/book/36085/chapter/313206091
Although unobservable, essential features can nonetheless affect classification by changing the evidence that observable features provide for category ...
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74
Learning exceptions to the rule in human and model via ...
https://www.nature.com/articles/s41598-021-00864-9
Category learning helps us process the influx of information we experience daily. A common category structure is “rule-plus-exceptions,” in ...
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https://www.nature.com/articles/s41598-021-00864-9
Category learning helps us process the influx of information we experience daily. A common category structure is “rule-plus-exceptions,” in ...
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75
Bloom's Taxonomy - Learning Classification system
https://thepeakperformancecenter.com/educational-learning/thinking/blooms-taxonomy/
Learner is able to examine and break information into components by identifying motives or causes as well as make inferences and find evidence to support ...
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https://thepeakperformancecenter.com/educational-learning/thinking/blooms-taxonomy/
Learner is able to examine and break information into components by identifying motives or causes as well as make inferences and find evidence to support ...
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76
Machine Learning Datasets - Papers With Code
https://paperswithcode.com/datasets
There are 6000 images per class with 5000 training and 1000 testing images per ... The Multi-Genre Natural Language Inference (MultiNLI) dataset has 433K ...
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https://paperswithcode.com/datasets
There are 6000 images per class with 5000 training and 1000 testing images per ... The Multi-Genre Natural Language Inference (MultiNLI) dataset has 433K ...
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77
Category Learning
https://ccnlab.fiu.edu/Category_Learning.html
Fast, accurate, and generalizable categorization of novel objects depends on the ability to extract some information from the objects that is relevant for a ...
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https://ccnlab.fiu.edu/Category_Learning.html
Fast, accurate, and generalizable categorization of novel objects depends on the ability to extract some information from the objects that is relevant for a ...
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78
Models and pre-trained weights — Torchvision 0.14 ... - PyTorch
https://pytorch.org/vision/stable/models.html
The classes of the pre-trained model outputs can be found at weights.meta["categories"] . Table of all available classification weights. Accuracies are reported ...
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https://pytorch.org/vision/stable/models.html
The classes of the pre-trained model outputs can be found at weights.meta["categories"] . Table of all available classification weights. Accuracies are reported ...
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79
Posters - NeurIPS 2022
https://nips.cc/Conferences/2022/Schedule?type=Poster
Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB ... MVP-N: A Dataset and Benchmark for Real-World Multi-View Object Classification.
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https://nips.cc/Conferences/2022/Schedule?type=Poster
Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB ... MVP-N: A Dataset and Benchmark for Real-World Multi-View Object Classification.
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80
KDnuggets: Data Science, Machine Learning, AI & Analytics
https://www.kdnuggets.com/
Data Science, Machine Learning, AI & Analytics.
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https://www.kdnuggets.com/
Data Science, Machine Learning, AI & Analytics.
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81
Support Vector Machine (SVM) Algorithm - Javatpoint
https://www.javatpoint.com/machine-learning-support-vector-machine-algorithm
Support Vector Machine or SVM is one of the most popular Supervised Learning algorithms, which is used for Classification as well as Regression problems.
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https://www.javatpoint.com/machine-learning-support-vector-machine-algorithm
Support Vector Machine or SVM is one of the most popular Supervised Learning algorithms, which is used for Classification as well as Regression problems.
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82
Natural Language AI - Google Cloud
https://cloud.google.com/natural-language
Analyze text with AI using pre-trained API or custom AutoML machine learning models to extract relevant entities, understand sentiment, and more.
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https://cloud.google.com/natural-language
Analyze text with AI using pre-trained API or custom AutoML machine learning models to extract relevant entities, understand sentiment, and more.
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83
Meta AI
https://ai.facebook.com/
GrokNet leverages a multi-task learning approach to train a single computer ... Further, we find that NACs can achieve an 8x speedup at inference time while ...
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https://ai.facebook.com/
GrokNet leverages a multi-task learning approach to train a single computer ... Further, we find that NACs can achieve an 8x speedup at inference time while ...
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84
Microsoft ML.NET 2 Adds Text Classification API - I Programmer
https://www.i-programmer.info/news/105-artificial-intelligence/15903-microsoft-mlnet-2-adds-text-classification-api.html
NET, its cross-platform, open source machine learning framework for . ... NET is a cross-platform framework for running Bayesian inference ...
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https://www.i-programmer.info/news/105-artificial-intelligence/15903-microsoft-mlnet-2-adds-text-classification-api.html
NET, its cross-platform, open source machine learning framework for . ... NET is a cross-platform framework for running Bayesian inference ...
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85
Top Machine Learning MCQ - InterviewBit
https://www.interviewbit.com/machine-learning-mcq/
An artificial neural network is a computational nonlinear model that is inspired by the brain. · ANN can perform tasks like classification, prediction, decision- ...
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https://www.interviewbit.com/machine-learning-mcq/
An artificial neural network is a computational nonlinear model that is inspired by the brain. · ANN can perform tasks like classification, prediction, decision- ...
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86
9 Types of Neural Networks: Applications, Pros, and Cons
https://www.knowledgehut.com/blog/data-science/types-of-neural-networks
We can classify and cluster data using neural networks, ... Sequence learning is a machine learning category that uses data sequences as ...
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https://www.knowledgehut.com/blog/data-science/types-of-neural-networks
We can classify and cluster data using neural networks, ... Sequence learning is a machine learning category that uses data sequences as ...
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87
YOLOv5 in PyTorch > ONNX > CoreML > TFLite - GitHub
https://github.com/ultralytics/yolov5
Inference with detect.py ... YOLOv5 release v6.2 brings support for classification model training, ... Classification Usage Examples Open In Colab ...
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https://github.com/ultralytics/yolov5
Inference with detect.py ... YOLOv5 release v6.2 brings support for classification model training, ... Classification Usage Examples Open In Colab ...
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88
Machine Learning for Beginners and Experts - TensorFlow Core
https://www.tensorflow.org/overview
Create a class for your model, then write the forward pass imperatively. Easily author custom layers, activations, and training loops. Run the “Hello World” ...
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https://www.tensorflow.org/overview
Create a class for your model, then write the forward pass imperatively. Easily author custom layers, activations, and training loops. Run the “Hello World” ...
→ Check Latest Keyword Rankings ←
89
30 Questions to test a data scientist on K-Nearest Neighbors ...
https://www.analyticsvidhya.com/blog/2017/09/30-questions-test-k-nearest-neighbors-algorithm/
If you are new to machine learning, make sure you test yourself on ... 11) Suppose, you want to predict the class of new data point x=1 and ...
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https://www.analyticsvidhya.com/blog/2017/09/30-questions-test-k-nearest-neighbors-algorithm/
If you are new to machine learning, make sure you test yourself on ... 11) Suppose, you want to predict the class of new data point x=1 and ...
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90
Machine Learning at the Edge - STMicroelectronics
https://www.electronicsmedia.info/2022/12/03/machine-learning-at-the-edge-stmicroelectronics/
Image classification: TFLM vs. X-CUBE-AI - Inference Time. In the first test, the application produced by X-CUBE-AI v7.1 has inference times ...
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https://www.electronicsmedia.info/2022/12/03/machine-learning-at-the-edge-stmicroelectronics/
Image classification: TFLM vs. X-CUBE-AI - Inference Time. In the first test, the application produced by X-CUBE-AI v7.1 has inference times ...
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91
Artificial intelligence | Definition, Examples, Types ... - Britannica
https://www.britannica.com/technology/artificial-intelligence
Are artificial intelligence and machine learning the same? ... To reason is to draw inferences appropriate to the situation.
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https://www.britannica.com/technology/artificial-intelligence
Are artificial intelligence and machine learning the same? ... To reason is to draw inferences appropriate to the situation.
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92
Descriptive Statistics: Definition, Overview, Types, Example
https://www.investopedia.com/terms/d/descriptive_statistics.asp
Descriptive statistics consists of three basic categories of measures: measures of ... Can Descriptive Statistics Be Used to Make Inference or Predictions?
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https://www.investopedia.com/terms/d/descriptive_statistics.asp
Descriptive statistics consists of three basic categories of measures: measures of ... Can Descriptive Statistics Be Used to Make Inference or Predictions?
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93
Generative AI: A Creative New World - Sequoia Capital
https://www.sequoiacap.com/article/generative-ai-a-creative-new-world/
A powerful new class of large language models is making it possible for ... shrink down the costs required to train and run inference.
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https://www.sequoiacap.com/article/generative-ai-a-creative-new-world/
A powerful new class of large language models is making it possible for ... shrink down the costs required to train and run inference.
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94
Abstract Category Learning - YouTube
https://www.youtube.com/watch?v=hi6r7vD7HPE
Jul 13, 2011
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https://www.youtube.com/watch?v=hi6r7vD7HPE
Jul 13, 2011
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95
State of Michigan Job Openings | . - Government Jobs
https://www.governmentjobs.com/careers/michigan
... Category: Corrections / Food Services / Public Safety / Trades ... performs cooking and food preparation tasks in a learning capacity, ...
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https://www.governmentjobs.com/careers/michigan
... Category: Corrections / Food Services / Public Safety / Trades ... performs cooking and food preparation tasks in a learning capacity, ...
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96
OpenAI API
https://openai.com/api/
Our advanced inference infrastructure provides extremely short response times. ... Easy to use and flexible enough to make machine learning teams more ...
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https://openai.com/api/
Our advanced inference infrastructure provides extremely short response times. ... Easy to use and flexible enough to make machine learning teams more ...
→ Check Latest Keyword Rankings ←
97
What are Large Language Models (LLMs)? Applications and ...
https://www.marktechpost.com/2022/11/29/what-are-large-language-models-llms-applications-and-types-of-llms/
Classifying text into predetermined categories is an example of supervised learning. Text with similar meanings can be clustered together ...
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https://www.marktechpost.com/2022/11/29/what-are-large-language-models-llms-applications-and-types-of-llms/
Classifying text into predetermined categories is an example of supervised learning. Text with similar meanings can be clustered together ...
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98
Interference of light - Condition and Types - BYJU'S
https://byjus.com/physics/coherent-sources/
Also, register to “BYJU'S – The Learning App” for loads of interactive, engaging Physics-related videos and an unlimited academic assist.
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https://byjus.com/physics/coherent-sources/
Also, register to “BYJU'S – The Learning App” for loads of interactive, engaging Physics-related videos and an unlimited academic assist.
→ Check Latest Keyword Rankings ←
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