Code

  • FSNSVQR : Feature selection for nonlinear support vector quantile regression.
  • TLRM :  Large Scale Non-convex Regression with Truncated Loss via Majorization-Minimization Algorithm.
  • LUHC :  LUHC is a Laplacian Unit-Hyperplane Learning for positive and unlabeled learning problem. This package provides a Demo Matlab code for LUHC.
  • RPTSVM :  RPTSVM is a regularization recursive projection twin support vector machine for binary classification. This package provides an implementation of the RPTSVM (PTSVM is a special case of RPTSVM) method by Matlab code.
  • L12DLDA :  L12DLDA is a L1-norm 2-dimension linear discriminant analysis for demension redundency. This package provides an implementation of the L12DLDA method by Matlab code
  • TWSVC :  TWSVC is a twin support vector machine for clustering. This package provides an implementation of the TWSVC method by Matlab code
  • LkPPC :  LkPPC is a local k-Proximal Plane Clustering method for clustering. This package provides an implementation of the LkPPC method by Matlab code
  • MPSVM :  MPSVM is a manifold proximal support vector machine for semi-supervised learnining problem. This package provides a Demo Matlab code for MPSVM
  • L1NPSVM :  L1NPSVM is a L1-norm nonparallel proximalsupport vector machine for binary classification. This package provides an implementation of the L1NPSVM method by Matlab code
  • WLTSVM :  WLTSVM is a weighted Lagrangian twin support vector machine for imbalanced data classification. This package provides an implementation of the WLTSVM method by Matlab code
  • FSTWSVM :  FSTWSVM is a feature selection method for twin support vector machines, including linear and nonlinear feature selection. This package provides an implementation of the FSTWSVM method by Matlab code
  • NHSVM :  NHSVM is a nonparallel hyperplane support vector machine for binary classification. This package provides an implementation of the NHSVM method by Matlab code
  • PCC :  PCC is a proximal classifier with consistency for binary classification. This package provides an implementation of the PCC method by Matlab code
  • PPWMs :  PPWMs is a tool for predicting palmitoylation sites based on protein sequence. This package provides an implementation of the PPWMs by C++ code
  • ETSVR :  ETSVR is a varepsilon-twin support vector machine for regression. This package provides an implementation of the ETSVR method by Matlab code
  • TWSVM :  TWSVM is a twin support vector machine for binary classification. This package provides an implementation of the TBSVM (TWSVM is a special case of TBSVM) method by Matlab code
  • STPMSVM :  STPMSVM is a smooth twin parametric-margin support vector machine for binary classification. This package provides an implementation of the STPMSVM method by Matlab code
  • RPTSVM :  RPTSVM is a regularization recursive projection twin support vector machine for binary classification. This package provides an implementation of the RPTSVM (PTSVM is a special case of RPTSVM) method by Matlab code
  • LSPTSVM :  LSPTSVM is a least squares recursive projection twin support vector machine for binary classification. This package provides an implementation of the LSPTSVM (only linear case) method by Matlab code
  • 2DLDAL1S :  Sparse L1-norm two dimensional linear discriminant analysis via the generalized elastic net regularization
  • RFDPC :  A Matlab code for Robust fitting distribution planes for clustering.
  • BLp2DLDA :  Robust bilateral Lp-norm two-dimensional linear discriminant analysis
  • 2DRLPP :  2DRLPP: Robust Two-Dimensional Locality Preserving Projection with Regularization
  • ESQSVR :  Extensive semi-quantitative regression
  • G2DLDA :  Generalized two-dimensional linear discriminant analysis with regularization
  • GLpNPSVM :  Generalized elastic net Lp-norm nonparallel support vector machine
  • kPPC :  k-Proximal Plane Clustering,
  • L1BLDA :  Robust Bhattacharyya bound linear discriminant analysis through an adaptive non-greedy algorithm
  • LpNPSVM :  Robust nonparallel proximal support vector machine with Lp-norm regularization.
  • LqLSSVM :  Feature selection via sparse $L_q$-norm least squares support vector machines for small size samples
  • LSTBSVC :  Clustering by twin support vector machine and least square twin support vector classifier with uniform output coding
  • LTSVM :  An efficient weighted Lagrangian twin support vector machine for imbalanced data classification
  • MBLDA :  MBLDA: a novel multiple between-class linear discriminant analysis
  • MDR :  Minimum deviation distribution machine for large scale regression
  • MFPC :  Multiple Flat Projections Clustering for Cross-manifold
  • MLSPTSVM :  Multiple recursive projection twin support vector machine for multi-class classification
  • MLTSVM :  Multi-label twin support vector machine for pattern classification
  • MVSVML1 :  Robust L1-norm multi-weight vector projection support vector machine for pattern recognition
  • NSVM :  Single Versus Union: Non-parallel Support Vector Machine Frameworks
  • PDLSSVM :  Joint sample and feature selection via sparse primal and dual LSSVM
  • PINSVR :  A novel parametric-insensitive nonparallel support vector machine for regression
  • RampTWSVC :  Ramp-based Twin Support Vector Clustering
  • RankSVM-PTM :  Prediction of acetylation and succinylation in proteins based on multi-label learning RankSVM
  • RDA :  Reversible discriminant analysis
  • RFDPC :  A general model for plane-based clustering with loss function
  • RSLDA :  Robust and sparse linear discriminant analysis via alternating direction method of multipliers
  • SGTSVM :  Stochastic gradient twin support vector machine for large scale data
  • RTBSVM :  Robust Rescaled Hinge Loss Twin Support Vector Machine for Imbalanced Noisy Classification
  • CLDA :  Capped norm linear discriminant analysis and its applications
  • SLSSVR :  Feature selection for high-dimensional regression via sparse LSSVR based on $L_p$-norm
  • GCLDA :  Generalized capped $l_{2,q}$ norm linear discriminant analysis with regularization
  • RNNL2BLDA :  A Matlab code for "Reverse nearest neighbors Bhattacharyya bound linear discriminant analysis for multimodal classification"
  • 2DBLDA :  A Matlab code for "Two-dimensional Bhattacharyya bound linear discriminant analysis with its applications".
  • LFDC :  LFDC is a Locally finite distance clustering with discriminative information for Clustering problem. This package provides a Demo Matlab code for LFDC.
  • 2DCLDA :  A Matlab code for Robust two-dimensional capped l2,1-norm linear discriminant analysis with regularization and its applications on face recognition
  •   Datasets

  • Crossplane Data :  A Matlab code for two dimensional crossplane (Xor) data generator used in TBSVM and NHSVM.
  • Real Estate Price Data :  A realife dataset with semi-quantitative information
  •   Tools

    [go top]