scholarly journals Reduced information feedback on a selection concept learning task

1973 ◽  
Vol 5 (4) ◽  
pp. 355-356 ◽  
Author(s):  
Richard P. McGlynn ◽  
Connie Schick
Keyword(s):  
Concept Learning ◽  
Learning Task ◽  
Information Feedback

Variables Affecting a Geographic Concept-Learning Task for Pre-School Children

1971 ◽  
Vol 70 (9) ◽  
pp. 551-554
Author(s):  
Peter H. Martorelk ◽  
Roger L. Wood
Keyword(s):  
Concept Learning ◽  
School Children ◽  
Learning Task

A Concept Learning-Based Patient-Adaptable Abnormal ECG Beat Detector for Long-Term Monitoring of Heart Patients

2011 ◽  
pp. 105-129 ◽  
Author(s):  
Peng Li ◽  
Kap L. Chan ◽  
Sheng Fu ◽  
Shankar M. Krishnan
Keyword(s):  
Concept Learning ◽  
Feedforward Neural Networks ◽  
Learning Task ◽  
Training Data ◽  
Support Vector ◽  
Heart Patients ◽  
Support Vector Classifier ◽  
Long Term Monitoring ◽  
Term Monitoring

n this chapter, a new concept learning-based approach is presented for abnormal ECG beat detection to facilitate long-term monitoring of heart patients. The novelty in our approach is the use of complementary concept—“normal” for the learning task. The concept “normal” can be learned by a v-support vector classifier (v-SVC) using only normal ECG beats from aspecific patient to relieve the doctors from annotating the training data beat by beat to train a classifier. The learned model can then be used to detect abnormal beats in the long-term ECG recording of the same patient. We have compared with other methods, including multilayer feedforward neural networks, binary support vector machines, and so forth. Experimental results on MIT/BIH arrhythmia ECG database demonstrate that such a patient-adaptable concept learning model outperforms these classifiers even though they are trained using tens of thousands of ECG beats from a large group of patients.

scholarly journals Certainty Is Primarily Determined by Past Performance During Concept Learning

Open Mind ◽  
2018 ◽  
Vol 2 (2) ◽  
pp. 47-60 ◽  
Author(s):  
Louis Martí ◽  
Francis Mollica ◽  
Steven Piantadosi ◽  
Celeste Kidd
Keyword(s):  
Concept Learning ◽  
Learning Task ◽  
Learning Curves ◽  
Regression Analyses ◽  
Learning Models ◽  
Past Performance ◽  
Statistical Inferences ◽  
Logical Concept ◽  
Subjective Reports ◽  
The Ideal

Prior research has yielded mixed findings on whether learners’ certainty reflects veridical probabilities from observed evidence. We compared predictions from an idealized model of learning to humans’ subjective reports of certainty during a Boolean concept-learning task in order to examine subjective certainty over the course of abstract, logical concept learning. Our analysis evaluated theoretically motivated potential predictors of certainty to determine how well each predicted participants’ subjective reports of certainty. Regression analyses that controlled for individual differences demonstrated that despite learning curves tracking the ideal learning models, reported certainty was best explained by performance rather than measures derived from a learning model. In particular, participants’ confidence was driven primarily by how well they observed themselves doing, not by idealized statistical inferences made from the data they observed.

Mothers' sensitivity to the competencies of their preschoolers on a concept-learning task

1996 ◽  
Vol 11 (3) ◽  
pp. 405-424 ◽  
Author(s):  
Linda Baker ◽  
Susan Sonnenschein ◽  
Mira Gilat
Keyword(s):  
Concept Learning ◽  
Learning Task

Paired-Associate Learning, False-Recognition Scores, and Performance in a Hierarchically Arranged Concept-Learning Task

1974 ◽  
Vol 35 (3) ◽  
pp. 1207-1210
Author(s):  
Fred W. Ohnmacht ◽  
Pauline C. Grippin ◽  
John O'Connor ◽  
Richard Brody
Keyword(s):  
Concept Learning ◽  
False Recognition ◽  
Paired Associate ◽  
Learning Task ◽  
Paired Associate Learning ◽  
Associate Learning ◽  
And Performance

This study evaluated the hypotheses that paired-associate learning would be negatively related to number of acquisition trials for simple concepts but not related to a complex one and that false recognition would be positively related to such acquisitions but most strongly to a relatively complex one. Data provided some support for these predictions.

Hypothesis behavior in a concept-learning task with probabilistic feedback.

1968 ◽  
Vol 76 (1, Pt.1) ◽  
pp. 160-165 ◽  
Author(s):  
Steven P. Rogers ◽  
Robert C. Haygood
Keyword(s):  
Concept Learning ◽  
Learning Task ◽  
Hypothesis Behavior
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