An Introduction to Machine Learning [E-Book] / by Miroslav Kubat.
This book presents basic ideas of machine learning in a way that is easy to understand, by providing hands-on practical advice, using simple examples, and motivating students with discussions of interesting applications. The main topics include Bayesian classifiers, nearest-neighbor classifiers, lin...
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Full text |
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Personal Name(s): | Kubat, Miroslav, author |
Imprint: |
Cham :
Springer International Publishing,
2015
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Physical Description: |
XIII, 291 p. 71 illus., 2 illus. in color. online resource. |
Note: |
englisch |
ISBN: |
9783319200101 |
DOI: |
10.1007/978-3-319-20010-1 |
Subject (ZB): | |
Subject (LOC): | |
Classification: |
- A Simple Machine-Learning Task
- Probabilities: Bayesian Classifiers
- Similarities: Nearest-Neighbor Classifiers
- Inter-Class Boundaries: Linear and Polynomial Classifiers
- Artificial Neural Networks
- Decision Trees
- Computational Learning Theory
- A Few Instructive Applications
- Induction of Voting Assemblies
- Some Practical Aspects to Know About
- Performance Evaluation.-Statistical Significance
- The Genetic Algorithm
- Reinforcement learning.