LIONbook: Machine Learning + Intelligent Optimization – completed, free personal download
This book combines two usually separated topics: machine learning and intelligent optimization, and does it with enough technical details to satisfy professionals, but also with concrete examples, vivid images, and fun. Buy a lowcost paperback or ebook (Kindle), or download a free PDF.
By Gregory Piatetsky, Mar 11, 2014.
LIONbook, is a new, just completed book, written by the developers of LionSolver software, Roberto Battiti and Mauro Brunato.
This book aims to combine two usually separated topics:
Both topics are technical and the book has appropriate equations to satisfy the analytics professionals. However, this book can also be read by nonprofessionals who want to understand the paradigm shift brought by machine learning and intelligent optimization methods. The book has plenty of concrete examples and vivid illustratons, and is fun to read!
The authors made this book freely available on the web for personal use at
intelligentoptimization.org/LIONbook/index.html
You can also buy a lowcost paperback version from Amazon or download ebook (Kindle format).
Contents:
1 Introduction 1
2 Lazy learning: nearest neighbors 9
3 Learning requires a method 15
4 Linear models 29
5 Mastering generalized linear leastsquares 41
6 Rules, decision trees, and forests 59
7 Ranking and selecting features 71
8 Specific nonlinear models 81
9 Neural networks, shallow and deep 93
10 Statistical Learning Theory and Support Vector Machines (SVM) 109
11 Democracy in machine learning 123
12 Topdown clustering: Kmeans 137
13 Bottomup (agglomerative) clustering 149
14 Selforganizing maps 157
15 Dimensionality reduction by linear transformations (projections) 165
16 Visualizing graphs and networks by nonlinear maps 179
17 Semisupervised learning 191
18 Automated improvements by local steps 203
19 Local Search and Reactive Search Optimization (RSO) 235
20 Continuous and Cooperative Reactive Search Optimization (CoRSO) 251
21 MultiObjective Reactive Search Optimization (MORSO) 265
22 Text and web mining 277
23 Collaborative filtering and recommendation 299
Bibliography 307
LIONbook, is a new, just completed book, written by the developers of LionSolver software, Roberto Battiti and Mauro Brunato.
This book aims to combine two usually separated topics:
 machine learning
 and intelligent optimization.
Both topics are technical and the book has appropriate equations to satisfy the analytics professionals. However, this book can also be read by nonprofessionals who want to understand the paradigm shift brought by machine learning and intelligent optimization methods. The book has plenty of concrete examples and vivid illustratons, and is fun to read!
The authors made this book freely available on the web for personal use at
intelligentoptimization.org/LIONbook/index.html
You can also buy a lowcost paperback version from Amazon or download ebook (Kindle format).
Contents:
1 Introduction 1
2 Lazy learning: nearest neighbors 9
3 Learning requires a method 15
4 Linear models 29
5 Mastering generalized linear leastsquares 41
6 Rules, decision trees, and forests 59
7 Ranking and selecting features 71
8 Specific nonlinear models 81
9 Neural networks, shallow and deep 93
10 Statistical Learning Theory and Support Vector Machines (SVM) 109
11 Democracy in machine learning 123
12 Topdown clustering: Kmeans 137
13 Bottomup (agglomerative) clustering 149
14 Selforganizing maps 157
15 Dimensionality reduction by linear transformations (projections) 165
16 Visualizing graphs and networks by nonlinear maps 179
17 Semisupervised learning 191
18 Automated improvements by local steps 203
19 Local Search and Reactive Search Optimization (RSO) 235
20 Continuous and Cooperative Reactive Search Optimization (CoRSO) 251
21 MultiObjective Reactive Search Optimization (MORSO) 265
22 Text and web mining 277
23 Collaborative filtering and recommendation 299
Bibliography 307
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