Titlebook: Machine Learning - EWSL-91; European Working Ses Yves Kodratoff Conference proceedings 1991 Springer-Verlag Berlin Heidelberg 1991 Logic Pr

偽造者

Machine Learning - EWSL-91978-3-540-46308-5Series ISSN 0302-9743 Series E-ISSN 1611-3349

商議

Cloudburst

Using plausible explanations to bias empirical generalization in weak theory domains,ations support a notion of ‘deep’ similarity and can provide substantial bias on the empirical modification of concepts. Several criteria that implement this bias are described, and an extended example illustrates how they lead to intelligent generalization behaviour.

戰(zhàn)役

Analytical negative generalization and empirical negative generalization are not cumulative: A case to be independent of the particular inductive learning algorithm considered (i.e., version spaces), thus helping clarify one aspect of the ill-understood relation between analytical generalization and empirical generalization.

使糾纏

monopoly

Using accuracy in scientific discovery,, this information can significantly improve not only the accuracy of the results but also the efficiency of the search algorithm. Several additional modifications to ABACUS to improve the robustness of the system without losing generality will also be described.

倒轉(zhuǎn)

On estimating probabilities in tree pruning,obabilities can be incorporated into error estimation, several trees pruned to various degrees can be generated, and the degree of pruning is not affected by the number of classes. These improvements are supported by experimental findings. .-probability-estimation also enables the combination of learning data obtained from various sources.

無(wú)王時(shí)期,

Antagonism

When does overfitting decrease prediction accuracy in induced decision trees and rule sets?,pt to uncover the conditions under which these techniques work as expected. One auxilliary result of importance is identification of conditions under which overfitting does . decrease predictive accuracy and hence in which it would be a mistake to apply simplification techniques, if predictive accuracy is the key goal.

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