TY  - BOOK
AU  - Mitchell,Tom M.(Tom Michael)
TI  - Machine learning
T2  - McGraw-Hill series in computer science
SN  - 0070428077
AV  - Q325.5 .M58 1997
PY  - 1997///,©1997
CY  - New York
PB  - The McGraw-Hill
KW  - Computer algorithms
KW  - Machine learning
N1  - Includes bibliographical references and index; 1. Introduction; --2. Concept Learning and the General-to-Specific Ordering; --3. Decision Tree Learning; --4. Artificial Neural Networks; --5. Evaluating Hypotheses; --6. Bayesian Learning; --7. Computational Learning Theory; --8. Instance-Based Learning; --9. Genetic Algorithms; --10. Learning Sets of Rules; --11. Analytical Learning; --12. Combining Inductive and Analytical Learning; --13. Reinforcement Learning
N2  - Mitchell covers the field of machine learning, the study of algorithms that allow computer programs to automatically improve through experience and that automatically infer general laws from specific data
ER  -