Dutt, V., & Gonzalez, C.: Making Instance-based Learning Theory Usable and Understand- able: The Instance-based Learning Tool. Computers in Human Behavior, 28(4), 1227-1240. doi: 10.1016/j.chb.2012.02.006, (2012).Dutt, V., & Gonzalez, C.: Making Instance-based Learning T heory ...
INSTANCE-BASED LEARNINGThis paper begins with a general theory of error in cross-validation testing of algorithms for supervised learning from examples. It is assumed that the examples are described by attribute-value pairs, where the values are symbolic. Cross-validation requires a set of training...
SIBL learns to select actions based upon se- quences of consecutive states. The algorithms rely primarily on sequential observations rather than a complete domain theory. We report the results of experiments on fixed-length and varying-length sequences. Four sequential similarity metrics are defined ...
Learning algorithms Learning Theory Machine Learning Statistical Learning References Aha, D.W. (1989a) Incremental, instance-based learning of independent and graded concept descriptions.Proceed-ings of the Sixth International Workshop on Machine Learning (pp.387-391) Ithaca, NY: Morgan Kaufmann....
The problem of instance selection for instance-based learning can be defined as “the isolation of the smallest set of instances that enable us to predict the class of a query instance with the same (or higher) accuracy than the original set” [4]. Another common task in data mining is ...
Instance-based learning algorithms do not maintain a set of abstractions derived from specific instances. This approach extends the nearest neighbor algorithm, which has large storage requirements. We describe how storage requirements can be significantly reduced with, at most, minor sacrifices in ...
Experiment 2 was a 10-session (two-week) extended practice study which was conducted to provide a strong test of instance-based learning as a sole mechanism for automaticity. Contrary to predictions of instance theory, the Search and Nonsearch conditions converged for the young adults. Consistent...
How People Make Their Own Environments: A Theory of Genotype --> Environment EffectsReduction Techniques for Instance-Based Learning AlgorithmsA Framework for Multiple-Instance LearningA framework for multiple-instance learning同义词 thing suggestion situation recommendation proposal practicality illus ...
A new method of instance-based learning for databases is proposed. We improve the current similarity measures in several ways using information theory. Similarity is defined on every possible attribute type in a database, and also the weight of each attribute is calculated automatically by the ...
The kNN algorithm is included in the family of instance based learning, in particular within the lazy learners, as it does not build a classification model but just stores all the training set [8]. Its classification rule is simple: for each new instance, assign the class according to the ...