Machine-learning inductive

One of the first attempts to build a knowledge base for synthetic organic reactions was made by Gelernter s group, through inductive and deductive machine learning [1]. Important work on this topic was also performed by Funatsu and his group [2]. 

Mingers, J., 1989. An Empirical Comparison of Pruning Methods for Decision Tree Induction. Machine Learning, 4, 221. 

Inductive learning by decision trees is a popular machine learning technique, particularly for solving classification problems, and was developed by Quinlan (1986). A decision tree depicting the input/output mapping learned from the data in Table I is shown in Fig. 22. The input information consists of pressure, temperature, and color measurements of... 

Inductive logic programming (ILP) is not a pharmacophore generation method by itself, but a subfield of the machine learning approach. In this field, other methods such as hidden Markov models, Bayesian learning, decision trees and logic programs are available. 

J.R. Quinlan, Induction of Decision Trees. Machine Learning, 1986, 1, 81-106. 

Document clustering is a form of unsupervised machine learning [28]. At its simplest and purest level, document clustering requires no prior knowledge or expectations about the contents and provides concept extraction [29] and knowledge navigation. Furthermore, concept extraction can seed an automatic derivation of classifications and serve as a method of ontology induction [30],... 

Cooper, G. F., and E. Herskovits. 1992. A Bayesian method for the induction of probabilistic networks from data. Machine Learning 9 309-47. 

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