Introduction to Machine Learning
-15%
portes grátis
Introduction to Machine Learning
Kubat, Miroslav
Springer International Publishing AG
08/2018
348
Mole
Inglês
9783319876696
15 a 20 dias
557
Descrição não disponível.
1 A Simple Machine-Learning Task.- 2 Probabilities: Bayesian Classifiers.- Similarities: Nearest-Neighbor Classifiers.- 4 Inter-Class Boundaries: Linear and Polynomial Classifiers.- 5 Artificial Neural Networks.- 6 Decision Trees.- 7 Computational Learning Theory.- 8 A Few Instructive Applications.- 9 Induction of Voting Assemblies.- 10 Some Practical Aspects to Know About.- 11 Performance Evaluation.- 12 Statistical Significance.- 13 Induction in Multi-Label Domains.- 14 Unsupervised Learning.- 15 Classifiers in the Form of Rulesets.- 16 The Genetic Algorithm.- 17 Reinforcement Learning.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
Bayesian classifiers;boosting;computational learning theory;decision trees;genetic algorithms;linear and polynomial classifiers;nearest neighbor classifier;neural networks;performance evaluation;reinforcement learning;statistical learning;time-varying classes, imbalanced representation;artificial intelligence;machine learning;data mining;deep learning;unsupervised learning
1 A Simple Machine-Learning Task.- 2 Probabilities: Bayesian Classifiers.- Similarities: Nearest-Neighbor Classifiers.- 4 Inter-Class Boundaries: Linear and Polynomial Classifiers.- 5 Artificial Neural Networks.- 6 Decision Trees.- 7 Computational Learning Theory.- 8 A Few Instructive Applications.- 9 Induction of Voting Assemblies.- 10 Some Practical Aspects to Know About.- 11 Performance Evaluation.- 12 Statistical Significance.- 13 Induction in Multi-Label Domains.- 14 Unsupervised Learning.- 15 Classifiers in the Form of Rulesets.- 16 The Genetic Algorithm.- 17 Reinforcement Learning.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
Bayesian classifiers;boosting;computational learning theory;decision trees;genetic algorithms;linear and polynomial classifiers;nearest neighbor classifier;neural networks;performance evaluation;reinforcement learning;statistical learning;time-varying classes, imbalanced representation;artificial intelligence;machine learning;data mining;deep learning;unsupervised learning
