Covering all the main approaches in state-of-the-art machine learning research, this will set a new standard as an introductory textbook.
An introductory textbook covering all the main approaches in state-of-the-art machine learning research.
Inhaltsverzeichnis
Prologue: a machine learning sampler; 1. The ingredients of machine learning; 2. Binary classification and related tasks; 3. Beyond binary classification; 4. Concept learning; 5. Tree models; 6. Rule models; 7. Linear models; 8. Distance-based models; 9. Probabilistic models; 10. Features; 11. In brief: model ensembles; 12. In brief: machine learning experiments; Epilogue: where to go from here; Important points to remember; Bibliography; Index.
