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数据挖掘的工具箱,最新版的,希望对做这方面研究的人有用

% Data Description Toolbox
% Version 1.11 23-Nov-2003
%
%Dataset construction
%--------------------
%isocset        true if dataset is one-class dataset
%gendatoc       generate a one-class dataset from two data matrices
%oc_set         change normal classif. problem to one-class problem
%target_class   extracts the target class from an one-class dataset
%make_outliers  create outlier data in a box around target class
%gendatgrid     create a grid dataset around a 2D dataset
%gendatout      create outlier data in a hypersphere around the
%               target data
%dd_crossval    cross-validation dataset creation
%
%Data preprocessing
%------------------
%myproxm        replacement for proxm.m
%kwhiten        rescale data to unit variance in kernel space
%gower          compute the gower similarities
%
%One-class classifiers
%---------------------
%random_dd      description which randomly assigns labels
%gauss_dd       data description using normal density
%rob_gauss_dd   robustified gaussian distribution
%mcd_gauss_dd   Minimum Covariance Determinant gaussian
%mog_dd         mixture of Gaussians data description
%parzen_dd      Parzen density data description
%
%autoenc_dd     auto-encoder neural network data description
%kcenter_dd     k-center data description
%kmeans_dd      k-means data description
%pca_dd         principal component data description
%som_dd         Self-Organizing Map data description
%
%nndd           nearest neighbor based data description
%knndd          K-nearest neighbor data description
%svdd           Support vector data description
%ksvdd          SVDD on general kernel matrices
%lpdd           linear programming data description
%dlpdd          distance-linear programming data description
%
%isocc          true if classifier is one-class classifier
%consistent_occ optimize the hyperparameter using consistency
%
%
%Error computation.
%-----------------
%dd_error       false positive and negative fraction of classifier
%dd_f1          F1 score computation
%dd_roc         computation of the Receiver-Operating Characterisic curve 
%dd_auc         error under the ROC curve
%dd_delta_aic   AIC error for density estimators
%dd_fp          compute false positives for given false negative
%               fraction
%simple_roc     basic ROC curve computation
%
%Plot functions.
%--------------
%plotroc        plot an ROC curve
%plotg          plot a 2D grid of function values
%plotw          plot a 2D real-valued output of classifier w
%
%Support functions.
%-----------------
%find_target    gives the indices of target and outlier objs from a dataset
%getoclab       returns numeric labels (+1/-1)
%dist2dens      map distance to posterior probabilities
%dd_threshold   give percentiles for a sample
%setthres       set the threshold for a one-class classifier
%randsph        create outlier data uniformly in a unit hypersphere
%makegriddat    auxiliary function for constructing grid data
%relabel        relabel a dataset
%center         center the kernel matrix in kernel space
%gausspdf       multi-variate Gaussian prob.dens.function
%mahaldist      Mahalanobis distance
%sqeucldistm    square Euclidean distance
%mogEM          EM procedure to optimize Mixture of Gaussians
%mogP           probability density of Mixture of Gaussians
%mykmeans       own implementation of the k-means clustering algorithm
%getfeattype    find the nominal and continuous features
%knn_optk       optimization of k for the knndd using leave-one-out
%volsphere      compute the volume of a hypersphere
%scale_range    compute a reasonable range of scales for a dataset
%
%
%Examples
%--------
%dd_ex1         show performance of nndd and svdd
%dd_ex2         show the performances of a list of classifiers
%dd_ex3         shows the use of the svdd and ksvdd
%dd_ex4         optimizes a hyperparameter using consistent_occ
%dd_ex5         shows the construction of lpdd from dlpdd
%
% Copyright: D.M.J. Tax, [e-mail]
% Faculty of Applied Physics, Delft University of Technology
% P.O. Box 5046, 2600 GA Delft, The Netherlands