Classification

Support Vector Machines , Logistic Regression , Decision Trees , Neural Networks , Deep Learning (Deep Neural Networks) , Levenberg-Marquardt with Bayesian Regularization , Restricted Boltzmann Machines , Sequence classification , Hidden Markov Classifiers and Hidden Conditional Random Fields

Regression

Multiple linear regression , Multivariate linear regression , polynomial regression , logarithmic regression. Logistic regression , multinomial logistic regression (softmax) and generalized linear models . L2-regularized L2-loss logistic regression , L2-regularized logistic regression , L1-regularized logistic regression , L2-regularized logistic regression in the dual form and regression support vector machines .

Clustering

K-Means , K-Modes , Mean-Shift , Gaussian Mixture Models , Binary Split , Deep Belief Networks , Restricted Boltzmann Machines . Clustering algorithms can be applied in arbitrary data, including images , data tables, videos and audio .

Distributions

Parametric and non-parametric estimation of more than 40 distributions. Univariate distributions such as Normal , Cauchy , Hypergeometric , Poisson , Bernoulli , and specialized distributions such as the Kolmogorov-Smirnov , Nakagami , Weibull , and Von-Mises distributions. Multivariate distributions such as the multivariate Normal , Multinomial , Independent , Joint and Mixture distributions.

Hypothesis Tests

More than 35 statistical hypothesis tests , including one way and two-way ANOVA tests , non-parametric tests such as the Kolmogorov-Smirnov test and the Sign Test for the Median , contingency table tests such as the Kappa test , with variations for multiple tables , as well as the Bhapkar and Bowker tests; and the more traditional Chi-Square , Z , F , T and Wald tests .

Kernel Methods

Kernel Support Vector Machines , Multi-class and Multi-label machines , Sequential Minimal Optimization , Least-Squares Learning , probabilistic learning , including special methods for linear machines such as LIBLINEAR's methods for Linear Coordinate Descent , Linear Newton Method , Probabilistic Coordinate Descent , Probabilistic Coordinate Descent in the Dual , Probabilistic Newton Method for L1 and L2 machines in both the dual and primal formulations .

Imaging

Interest and feature point detectors such as Harris , FREAK , SURF , and FAST . Grey-level Co-occurrence matrices , Border following , Bag-of-Visual-Words (BoW) , RANSAC-based homography estimation , integral images , haralick textural feature extraction , and dense descriptors such as histogram of oriented gradients (HOG) and Local Binary Pattern (LBP) . Several image filters for image processing applications such as difference of Gaussians , Gabor , Niblack and Sauvola thresholding .

Audio and Signal

Load, parse, save, filter and transform audio signals , such as applying audio processing filters in both space and frequency domain . WAV files , audio capture , time-domain filters such as envelope , high-pass , low-pass , wave rectification filters. Frequency-domain operators such as differential rectification filter and comb filter with Dirac's delta functions . Signal generators for Cosine , Impulse , Square signals.

Vision

Real-time face detection and tracking , as well as general methods for detecting , tracking and transforming objects in image streams . Contains cascade definitions , Camshift and Dynamic Template Matching trackers . Includes pre-created classifiers for human faces and some facial features such as noses .