User:Taser/Books/Machine Learning Vol-2

Machine Learning

 * Learning Theory
 * Computational learning theory
 * Version space
 * Probably approximately correct learning
 * Vapnik–Chervonenkis theory
 * Shattering (machine learning)
 * VC dimension
 * Minimum description length
 * Bondy's theorem
 * Inferential theory of learning
 * Rademacher complexity
 * Teaching dimension
 * Subclass reachability
 * Sample exclusion dimension
 * Unique negative dimension
 * Uniform convergence (combinatorics)
 * Witness set


 * Support Vector Machines
 * Kernel methods
 * Support vector machine
 * Structural risk minimization
 * Empirical risk minimization
 * Kernel trick
 * Least squares support vector machine
 * Relevance vector machine
 * Sequential minimal optimization
 * Structured SVM


 * Regression analysis
 * Outline of regression analysis
 * Regression analysis
 * Dependent and independent variables
 * Linear model
 * Linear regression
 * Least squares
 * Linear least squares (mathematics)
 * Local regression
 * Additive model
 * Antecedent variable
 * Autocorrelation
 * Backfitting algorithm
 * Bayesian linear regression
 * Bayesian multivariate linear regression
 * Binomial regression
 * Canonical analysis
 * Censored regression model
 * Coefficient of determination
 * Comparison of general and generalized linear models
 * Compressed sensing
 * Conditional change model
 * Controlling for a variable
 * Cross-sectional regression
 * Curve fitting
 * Deming regression
 * Design matrix
 * Difference in differences
 * Dummy variable (statistics)
 * Errors and residuals in statistics
 * Errors-in-variables models
 * Explained sum of squares
 * Explained variation
 * First-hitting-time model
 * Fixed effects model
 * Fraction of variance unexplained
 * Frisch–Waugh–Lovell theorem
 * General linear model
 * Generalized additive model
 * Generalized additive model for location, scale and shape
 * Generalized estimating equation
 * Generalized least squares
 * Generalized linear array model
 * Generalized linear mixed model
 * Generalized linear model
 * Growth curve
 * Guess value
 * Hat matrix
 * Heckman correction
 * Heteroscedasticity-consistent standard errors
 * Hosmer–Lemeshow test
 * Instrumental variable
 * Interaction (statistics)
 * Isotonic regression
 * Iteratively reweighted least squares
 * Kitchen sink regression
 * Lack-of-fit sum of squares
 * Leverage (statistics)
 * Limited dependent variable
 * Linear probability model
 * Mallows's Cp
 * Mean and predicted response
 * Mixed model
 * Moderation (statistics)
 * Moving least squares
 * Multicollinearity
 * Multiple correlation
 * Multivariate probit
 * Multivariate adaptive regression splines
 * Newey–West estimator
 * Non-linear least squares
 * Nonlinear regression


 * Logistic Regression
 * Logit
 * Multinomial logit
 * Logistic regression


 * Bio-inspired Methods
 * Bio-inspired computing


 * Evolutionary Algorithms
 * Evolvability (computer science)
 * Evolutionary computation
 * Evolutionary algorithm
 * Genetic algorithm
 * Chromosome (genetic algorithm)
 * Crossover (genetic algorithm)
 * Fitness function
 * Evolutionary data mining
 * Genetic programming
 * Learnable Evolution Model


 * Neural Networks
 * Neural network
 * Artificial neural network
 * Artificial neuron
 * Types of artificial neural networks
 * Perceptron
 * Multilayer perceptron
 * Activation function
 * Self-organizing map
 * Attractor network
 * ADALINE
 * Adaptive Neuro Fuzzy Inference System
 * Adaptive resonance theory
 * IPO underpricing algorithm
 * ALOPEX
 * Artificial Intelligence System
 * Autoassociative memory
 * Autoencoder
 * Backpropagation
 * Bcpnn
 * Bidirectional associative memory
 * Biological neural network
 * Boltzmann machine
 * Restricted Boltzmann machine
 * Cellular neural network
 * Cerebellar Model Articulation Controller
 * Committee machine
 * Competitive learning
 * Compositional pattern-producing network
 * Computational cybernetics
 * Computational neurogenetic modeling
 * Confabulation (neural networks)
 * Cortical column
 * Counterpropagation network
 * Cover's theorem
 * Cultured neuronal network
 * Dehaene-Changeux Model
 * Delta rule
 * Early stopping
 * Echo state network
 * The Emotion Machine
 * Evolutionary Acquisition of Neural Topologies
 * Extension neural network
 * Feed-forward
 * Feedforward neural network
 * Generalized Hebbian Algorithm
 * Generative topographic map
 * Group method of data handling
 * Growing self-organizing map
 * Memory-prediction framework
 * Helmholtz machine
 * Hierarchical temporal memory
 * Hopfield network
 * Hybrid neural network
 * HyperNEAT
 * Infomax
 * Instantaneously trained neural networks
 * Interactive Activation and Competition
 * Leabra
 * Learning Vector Quantization
 * Lernmatrix
 * Linde–Buzo–Gray algorithm
 * Liquid state machine
 * Long short term memory
 * Madaline
 * Modular neural networks
 * MoneyBee
 * Neocognitron
 * Nervous system network models
 * NETtalk (artificial neural network)
 * Neural backpropagation
 * Neural coding
 * Neural cryptography
 * Neural decoding
 * Neural gas
 * Neural Information Processing Systems
 * Neural modeling fields
 * Neural oscillation
 * Neurally controlled animat
 * Neuroevolution of augmenting topologies
 * Neuroplasticity
 * Ni1000
 * Nonspiking neurons
 * Nonsynaptic plasticity
 * Oja's rule
 * Optical neural network
 * Phase-of-firing code
 * Promoter based genetic algorithm
 * Pulse-coupled networks
 * Quantum neural network
 * Radial basis function
 * Radial basis function network
 * Random neural network
 * Recurrent neural network
 * Reentry (neural circuitry)
 * Reservoir computing
 * Rprop
 * Semantic neural network
 * Sigmoid function
 * SNARC
 * Softmax activation function
 * Spiking neural network
 * Stochastic neural network
 * Synaptic plasticity
 * Synaptic weight
 * Tensor product network
 * Time delay neural network
 * U-Matrix
 * Universal approximation theorem
 * Winner-take-all
 * Winnow (algorithm)


 * Reinforcement learning
 * Reinforcement learning
 * Markov decision process
 * Bellman equation
 * Q-learning
 * Temporal difference learning
 * SARSA
 * Multi-armed bandit
 * Apprenticeship learning
 * Predictive learning


 * Text Mining
 * Text mining
 * Natural language processing
 * Document classification
 * Bag of words model
 * N-gram
 * Part-of-speech tagging
 * Sentiment analysis
 * Information extraction
 * Topic model
 * Concept mining
 * Semantic analysis (machine learning)
 * Automatic summarization
 * Automatic distillation of structure
 * String kernel
 * Biomedical text mining
 * Never-Ending Language Learning


 * Structure Mining
 * Structure mining
 * Structured learning
 * Structured prediction
 * Sequence mining
 * Sequence labeling
 * Process mining


 * Advanced Learning Tasks
 * Multi-label classification
 * Classifier chains
 * Web mining
 * Anomaly detection
 * Anomaly Detection at Multiple Scales
 * Local outlier factor
 * Novelty detection
 * GSP Algorithm
 * Optimal matching
 * Record linkage
 * Meta learning (computer science)
 * Learning automata
 * Learning to rank
 * Multiple-instance learning
 * Statistical relational learning
 * Relational classification
 * Data stream mining
 * Alpha algorithm
 * Syntactic pattern recognition
 * Multispectral pattern recognition
 * Algorithmic learning theory
 * Deep learning
 * Bongard problem
 * Learning with errors
 * Parity learning
 * Inductive transfer
 * Granular computing
 * Conceptual clustering
 * Formal concept analysis
 * Biclustering
 * Information visualization
 * Co-occurrence networks


 * Applications
 * Problem domain
 * Recommender system
 * Collaborative filtering
 * Profiling (information science)
 * Speech recognition
 * Stock forecast
 * Activity recognition
 * Data Analysis Techniques for Fraud Detection
 * Molecule mining
 * Predictive behavioral targeting
 * Proactive Discovery of Insider Threats Using Graph Analysis and Learning
 * Robot learning
 * Computer vision
 * Facial recognition system
 * Outlier detection
 * Anomaly detection
 * Novelty detection


 * Software
 * R (programming language)
 * MapReduce
 * Oracle Data Mining
 * Pentaho
 * Mallet (software project)
 * Orange (software)
 * Learning Based Java
 * Scikit-learn
 * Waffles (machine learning)
 * Apache Mahout
 * Data Applied
 * Data Mining Extensions
 * ELKI
 * Feature Selection Toolbox
 * Monte Carlo Machine Learning Library (MCMLL)
 * Neural network software
 * Software mining