User:Aplegat/Books/Math
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Math
- Analysis of variance
- Analytic hierarchy process
- Analytic network process
- Ant colony optimization algorithms
- Artificial intelligence
- Artificial neural network
- Association rule learning
- Backtracking
- Backward induction
- Bayes estimator
- Bayesian network
- Bees algorithm
- Bellman equation
- Bellman–Ford algorithm
- Best linear unbiased prediction
- Bilevel optimization
- BIRCH (data clustering)
- Bootstrap aggregating
- Bootstrapping
- Boyer–Moore string search algorithm
- Canadian traveller problem
- Canonical correlation
- Cellular automaton
- Characteristic function (probability theory)
- Cholesky decomposition
- Cluster analysis
- Clustering high-dimensional data
- Confidence interval
- Confrontation analysis
- Consensus clustering
- Constrained optimization
- Convex optimization
- Conway's Game of Life
- Cooperative game
- Correlation clustering
- Correspondence analysis
- Cramér–Rao bound
- Critical path method
- Critical point (mathematics)
- Cutting stock problem
- Damerau–Levenshtein distance
- Decision tree
- Decision tree learning
- Default logic
- Derivative
- Design of experiments
- Determinant
- Dijkstra's algorithm
- Discrete choice
- Duality (optimization)
- Dynamic programming
- Eigendecomposition of a matrix
- Eigenvalues and eigenvectors
- Empirical Bayes method
- Ensemble learning
- Errors and residuals in statistics
- Estimator
- Expectation–maximization algorithm
- Extensive-form game
- Factor analysis
- Feature learning
- Finite-state machine
- Fisher information
- Fixed effects model
- Ford–Fulkerson algorithm
- Game theory
- Gauss–Markov theorem
- General linear model
- Generalized assignment problem
- Generalized linear model
- Generalized method of moments
- Genetic algorithm
- Genetic programming
- Gini coefficient
- Graph coloring
- Graph theory
- Greedy algorithm
- Hessian matrix
- Hungarian algorithm
- Identifiability
- Inductive logic programming
- Information gain in decision trees
- Information retrieval
- Instrumental variable
- Integer programming
- Integral
- Interior point method
- Jacobian matrix and determinant
- Jeep problem
- Job shop scheduling
- Kalman filter
- Karush–Kuhn–Tucker conditions
- Kernel method
- Kernel regression
- Knapsack problem
- Knowledge representation and reasoning
- Knuth–Morris–Pratt algorithm
- Kullback–Leibler divergence
- Lagrange multiplier
- Lagrangian relaxation
- Law of cosines
- Law of cotangents
- Law of sines
- Law of tangents
- Least absolute deviations
- Least squares
- Leibniz integral rule
- Likelihood function
- Likelihood principle
- Linear complementarity problem
- Linear discriminant analysis
- Linear programming
- Linear regression
- Linear-fractional programming
- Lloyd's algorithm
- Local regression
- Logistic regression
- Low-rank approximation
- LU decomposition
- M-estimator
- Machine translation
- Markov chain
- Markov decision process
- Mathematical optimization
- Matrix calculus
- Maximum flow problem
- Maximum likelihood
- Mean and predicted response
- Memetic algorithm
- Metropolis–Hastings algorithm
- Minimax
- Minimum-variance unbiased estimator
- Mixed logit
- Mixed model
- Mixture model
- Multi-objective optimization
- Multi-task learning
- Multicriteria classification
- Multilevel model
- Multinomial logistic regression
- Multiple correspondence analysis
- Multiple integral
- Multiple-criteria decision analysis
- Naive Bayes classifier
- Nash equilibrium
- Natural language processing
- Nearest neighbor search
- Nelder–Mead method
- Newsvendor model
- Newton's method
- No free lunch in search and optimization
- Non-linear least squares
- Non-negative least squares
- Nonlinear programming
- Nonlinear regression
- Nonparametric regression
- Normal-form game
- NP-complete
- Observed information
- Odds algorithm
- Optimal control
- Optimal design
- Optimal stopping
- Ordered logit
- Ordinal optimization
- Ordinary differential equation
- Ordinary least squares
- Orthogonality principle
- P versus NP problem
- Parallel metaheuristic
- Pareto efficiency
- Parsing
- Partial correlation
- Partial derivative
- Partial differential equation
- Partial least squares regression
- Particle swarm optimization
- Pattern recognition
- Poisson regression
- Principal component analysis
- Principal component regression
- Probit model
- Program evaluation and review technique (PERT)
- Proofs of trigonometric identities
- Pythagorean theorem
- QR decomposition
- Quadratic programming
- Quantile regression
- Random effects model
- Random forest
- Rank factorization
- Rao–Blackwell theorem
- Recursive Bayesian estimation
- Regression analysis
- Regression model validation
- Reinforcement learning
- Ridge detection
- Robust optimization
- Robust regression
- Score (statistics)
- Second partial derivative test
- Seemingly unrelated regressions
- Self-organizing map
- Semi-supervised learning
- Semidefinite programming
- Semiparametric regression
- Sensitivity and specificity
- Shape optimization
- Similarity learning
- Simplex algorithm
- Simpson's paradox
- Simulated annealing
- Simultaneous game
- Singular value decomposition
- Smoothing spline
- Sorting algorithm
- Stable marriage problem
- Stein's unbiased risk estimate
- Stochastic process
- Stochastic programming
- Stress majorization
- Structural equation modeling
- Subgradient method
- Sufficient statistic
- Supervised learning
- Support vector machine
- Surface integral
- Swarm intelligence
- Tabu search
- Tikhonov regularization
- Total derivative
- Transduction (machine learning)
- Travelling salesman problem
- Trend estimation
- Trigonometry
- Triple product rule
- Unsupervised learning
- Volume element
- Voronoi diagram