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Margin classifier Probabilistic classification K-means clustering One-class classification Feature learning Neighbourhood components analysis Sequence labeling Platt scaling Nearest neighbor search Linear classifier Quadratic classifier Kernel perceptron Large margin nearest neighbor Multiclass classification Relevance vector machine Probabilistic neural network Margin Nearest-neighbor chain algorithm Kernel embedding of distributions Multi-label classification Nested sampling algorithm Linear predictor function Nearest-neighbor interpolation Approximate bayesian computation Feature selection Manifold regularization Hierarchical clustering Naive bayes classifier Hierarchical dirichlet process Supervised learning Local optimum Learning curve Linear discriminant analysis Minimum mean square error Cluster analysis Delta rule Least mean squares filter Instance-based learning Polynomial kernel M-theory Learning rate Maximum likelihood estimation Label propagation algorithm Loss functions for classification K-nearest neighbors algorithm Jenks natural breaks optimization Similarity measure Iterative method Precision and recall Conformal prediction Structured prediction Regression analysis Bayes classifier Fisher kernel Symbolic regression Sample complexity Grammar induction Gradient descent Recursive bayesian estimation Latent dirichlet allocation Feature extraction Moving least squares Feature Approximation algorithm Hellinger distance Mean shift Closeness centrality Lasso Closest pair of points problem Early stopping Perceptron Conditional random field Normality test Generalized least squares Linear regression Particle swarm optimization Recursive least squares filter Centroidal voronoi tessellation Prediction interval Minimax approximation algorithm Helmholtz machine Spectral clustering Gibbs sampling Recursive neural network Root-mean-square deviation Deep belief network Likelihood function Representer theorem Hyperparameter Hinge loss Temporal difference learning Statistical distance Nonlinear regression Knowledge graph embedding Graph neural network Empirical risk minimization Flow-based generative model Delta method Latent class model Decision tree learning

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