Category:Machine learning

A

• [+] Artificial intelligence conferences (8 P)

B

• [+] Bayesian networks (12 P)

C

• [+] Classification algorithms (1 C, 61 P)

D

• [+] Decision trees (16 P)

E

• [+] Ensemble learning (13 P)
• [+] Evolutionary algorithms (3 C, 33 P, 3 F)

K

• [+] Kernel methods for machine learning (7 P)

L

• [+] Learning in computer vision (5 P)

N

• [+] Neural networks (1 C, 94 P, 1 F)

R

• [+] Machine learning researchers (28 P)

A

• ALOPEX
• Accuracy paradox
• Activity recognition
• Adjusted Mutual Information
• Adjusted rand index
• Algorithmic learning theory
• Algorithmic inference
• Alpha (machine learning)
• Alternating decision tree
• Analogical modeling
• Apprenticeship learning
• Artificial neural network
• Auto-encoder

B

• Backpropagation
• Bag of words model
• Base rate
• Bipropagation
• Bondy's theorem
• Bongard problem
• Bootstrap aggregating
• Bootstrapping (machine learning)
• Bregman divergence

C

• CBCL (MIT)
• CIML community portal
• CN2 algorithm
• Calibration (statistics)
• Canopy clustering algorithm
• Cascade correlation algorithm
• Category utility
• Class membership probabilities
• Cluster analysis
• Cluster-weighted modeling
• Co-training
• Compositional pattern-producing network
• Computational learning theory
• Concept class
• Concept drift
• Concept learning
• Conceptual clustering
• Conditional random field
• Confusion matrix
• Constructive induction
• Cover's theorem
• Cross-validation (statistics)
• Cross-entropy method
• Crossover (genetic algorithm)
• Curse of dimensionality

D

• Data Applied
• Data Pre-processing
• DBSCAN
• Decision lists
• Decision rules
• Dendrogram
• Deterministic policy
• Dimension reduction
• Discriminative model
• Document classification
• Dominance-based Rough Set Approach
• Dynamic time warping

E

• Eager learning
• Elastic Matching
• Elbot
• Ensembles of classifiers
• EURASIP Journal on Advances in Signal Processing

E cont.

• Evolutionary algorithm
• Evolvability (computer science)
• Expectation propagation
• Expectation-maximization algorithm
• Explanation-based learning
• Exponential mechanism (differential privacy)

F

• FLAME clustering
• FastICA
• Feature vector
• Feature extraction
• Feature selection
• First Order Inductive Learner
• Formal concept analysis
• Forward-backward algorithm
• Function approximation

G

• Gaussian process
• Gaussian process emulator
• General Architecture for Text Engineering
• Generalization error
• Generative model
• Generative topographic map
• Genetic Algorithm for Rule Set Production
• Gittins index
• Glivenko–Cantelli theorem
• GoldenGem
• Grammar induction
• Granular computing
• Group method of data handling
• Growing self-organizing map

H

• Helmholtz machine
• Hidden Markov model
• Hierarchical hidden Markov model
• Hierarchical temporal memory

I

• IAPR
• ID3 algorithm
• Inductive bias
• Inductive logic programming
• Inductive transfer
• Information Fuzzy Networks
• Information bottleneck method
• Instance-based learning
• International Conference on Machine Learning
• Iris flower data set

J

• Jabberwacky
• Java Machine Learning Library
• Journal of Machine Learning Research

K

• K-means clustering
• K-means++
• K-medoids
• K-nearest neighbor algorithm
• Kernel methods
• Kernel principal component analysis
• Kernel adaptive filter
• Kernel trick
• Knowledge discovery
• Knowledge integration

L

• Language Acquisition Device (computer)
• Layered hidden Markov model
• Lazy learning
• Leabra
• Learning Automata
• Learning Vector Quantization
• Learning classifier system
• Learning to rank

L cont.

• Learning with errors
• Linde-Buzo-Gray algorithm
• List of machine learning algorithms
• Locally weighted regression
• Logistic model tree
• LogitBoost

M

• Machine Learning (journal)
• Machine learning
• Mallet (software project)
• Margin Infused Relaxed Algorithm
• Margin classifier
• Markov decision process
• Matthews correlation coefficient
• MeeMix
• Message-passing method
• Meta learning (computer science)
• Minimum redundancy feature selection
• Mixture model
• Multi-armed bandit
• Multi-task learning
• Multiple-instance learning

N

• Nearest neighbor search
• Neural Information Processing Systems
• Neural modeling fields
• Non-negative matrix factorization
• Nonlinear dimensionality reduction
• Novelty detection
• Numenta

O

• OPTICS algorithm
• Offline learning
• One-class classification
• Online learning model
• Online machine learning
• Overfitting

P

• PROGOL
• Pachinko machine
• Parity learning
• Partially observable Markov decision process
• Pattern recognition
• Perceptron
• Predictive learning
• Predictive state representation
• Premature convergence
• Principal component analysis
• Principle of maximum entropy
• Prior knowledge for pattern recognition
• Probability matching
• Probably approximately correct learning

Q

• Q-learning
• Quadratic classifier
• Quadratic unconstrained binary optimization

R

• Rademacher complexity
• Radial basis function network
• Rand index
• Random forest
• Random multinomial logit
• RapidMiner
• Regularization (mathematics)
• Reinforcement learning
• Relevance vector machine
• Robot learning
• Rough set