Encyclopedia of Machine Learning and Data Mining /
| Autor Corporativo: | |
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| Otros Autores: | , |
| Formato: | eBook |
| Lenguaje: | English |
| Publicado: |
New York, NY :
Springer US : Imprint: Springer,
2017.
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| Edición: | 2nd ed. 2017. |
| Materias: |
Tabla de Contenidos:
- Abduction
- Adaptive Resonance Theory
- Anomaly Detection
- Bayes Rule
- Case-Based Reasoning
- Categorical Data Clustering
- Causality
- Clustering from Data Streams
- Complexity in Adaptive Systems
- Complexity of Inductive Inference
- Computational Complexity of Learning
- Confusion Matrix
- Connections Between Inductive Inference and Machine Learning
- Covariance Matrix
- Decision List
- Decision Lists and Decision Trees
- Decision Tree
- Deep Learning
- Density-Based Clustering
- Dimensionality Reduction
- Document Classification
- Dynamic Memory Model
- Empirical Risk Minimization
- Error Rate
- Event Extraction from Media Texts
- Evolutionary Clustering
- Evolutionary Computation in Economics
- Evolutionary Computation in Finance
- Evolutionary Computational Techniques in Marketing
- Evolutionary Feature Selection and Construction
- Evolutionary Kernel Learning
- Evolutionary Robotics
- Expectation Maximization Clustering
- Expectation Propagation
- Feature Construction in Text Mining
- Feature Selection
- Feature Selection in Text Mining
- Gaussian Distribution
- Gaussian Process
- Generative and Discriminative Learning
- Grammatical Inference
- Graphical Models
- Hidden Markov Models
- Inductive Inference
- Inductive Logic Programming
- Inductive Programming
- Inductive Transfer
- Inverse Reinforcement Learning
- Kernel Methods
- K-Means Clustering
- K-Medoids Clustering
- K-Way Spectral Clustering
- Learning Algorithm Evaluation
- Learning Graphical Models
- Learning Models of Biological Sequences
- Learning to Rank
- Learning Using Privileged Information
- Linear Discriminant
- Linear Regression
- Locally Weighted Regression for Control
- Machine Learning and Game Playing
- Manhattan Distance
- Maximum Entropy Models for Natural Language Processing
- Mean Shift
- Metalearning
- Minimum Description Length Principle
- Minimum Message Length
- Mixture Model
- Model Evaluation
- Model Trees
- Multi Label Learning
- Naïve Bayes
- Occam's Razor
- Online Controlled Experiments and A/B Testing
- Online Learning
- Opinion Stream Mining
- PAC Learning
- Partitional Clustering
- Phase Transitions in Machine Learning.