Soft Independent Modeling of Class Analogy (SIMCA) by Cleiton Nunes

M-files for classes modeling and prediction by SIMCA (chemometrics, classification, simca)

simca.m

simcapred.m

Improved Distance Evaluation (IDE) by Behrad Bagheri

This method could be implemented for feature selection in classification problems. (feature selection, signal processing, classification)

[scores indices selected duration]=IDE2(data,classes,thresh...

Hot to run WEKA classifiers within MATLAB by Gustavo

This is an example on how to select and pass parameters to Weka from MATLAB (weka, machine learning, classification)

RunWekaFromMATLAB.m

A road to classification in high dimensional space: the regularized optimal affine discriminant by Yang Feng

A powerful method for binary classification in high dimensional space (classification, statistics, optimization)

[Sigma]=eqcor(p,rho)

analyzeReal(traindata, testdata)

lda(x, y, xtest, ytest)

Similarity classifier with OWA operators by Pasi Luukka

Toolbox presents vector based classification method which uses similarity measures and OWA operators (classification, fuzzy, biotech)

[Classification_accuracy,p1,m1,classes]=simclass(datalearn,...

[Mean_accuracy, Variance,p1,m1,Means,Vars,Maxsf,Minsf]=simo...

calcfit(data, ideals, y)

colAUC by Jaroslaw Tuszynski

Calculates Area under ROC curve (AUC) for a vector or for each column of a matrix. (roc, auc, statistics)

Tutorial for colAUC Function and Package

avrRank(x)

colAUC.m

Ensemble Toolbox by Mohammad Ali Bagheri

This toolbox provides some combination methods to fuse an ensemble of classifiers (classification, ensemble of classifie..., multiple classifier s...)

...

Ensemble_decision=CombineCLFs(CombinitionMethod,...

[Patterns,Targets,V_Targets]=LoadData(dataset,scale)

Credit Scoring demo by Hanan Kavitz

This is a demo that uses boosting to do credit scoring of German customers. (statistics, boosting, classification)

creditRatingGui(varargin)

CNN - Convolutional neural network class by Mihail Sirotenko

This project provides matlab class for implementation of convolutional neural networks. (neural network, machine learning, classification)

back_conv2(FM,e,K,type)

back_subsample(e, ratio)

cnet_tool(varargin)

Análise de Agrupamento Hierárquico (HCA) by Carlos Diego Lima de Albuquerque

As distâncias Euclidianas são calculadas e agrupamento é feito na através da média. (chemometrics, classification, hierarquical cluster ...)

hca.m

K Nearest Neighbor by Wei LI

KNN with configurable label prior, chuncking calculation for large data, and estimation of posterior (classification)

knn(train, trlabel ,probe, k ,opt)

Análise de Componentes Principais (PCA) by Carlos Diego Lima de Albuquerque

Emprega a PCA nos dados. (chemometrics, principal components ..., classification)

pca_biplot.m

Pré-Processamento dos dados by Carlos Diego Lima de Albuquerque

Processa os dados através das colunas. (chemometrics, classification, preprocessing)

prep.m

Decision Trees and Predictive Models with cross-validation and ROC analysis plot by Andrea Padoan

This code implements a classification tree and plots the ROC curves for each target class (classification tree, classification, decision tree)

BestTree (t, X, y, nsamples)

CalculateFeaturesImportance.m

CalculateOutcomeGroups (y)

Performance Measures for Classification by Barnan Das

This function evaluates the common performance measures for classification models. (performance measures, machine learning, classification)

Evaluate(ACTUAL,PREDICTED)

A probabilistic model of classifier competence by Tomasz Woloszynski

Classifier competence based on full vector of class supports and probabilistic modelling. (competence, probabilistic modelin..., ensemble)

ccprmod(d,j,varargin)

Confusion matrix / Matching matrix along with Precision, Sensitivity, Specificity and Model Accuracy by Avinash Uppuluri

CFMATRIX2 calculates the confusion matrix and related parameters for a classification algo. (statistics, probability, confusion matrix)

cfmatrix2(actual, predict, classlist, per, printout)

Sparse representations classifier by Bilwaj Gaonkar

Kernel version of the sparse representations classifier implemented with CVX (classification, sparse representation...)

[A]=sparse_represent(Test,Train,sp_level)

[a]=sparse_represent_kernelized(K_y,K_Tr,K_te,sp_level)

[predictions,src_scores,uniqlabels]=src(Traindata,Trainlabe...

Hidden Markov modelling of contourlet transforms for art authentication by Robert Jacobsen

Fits hidden Markov models to contourlet transform and use these for classification of images (hmt, em algorithm, classification)

EM(tree, model, minval, minval_sd)

HMTinit(coef, minval)

add_number(C, font_size)

Classic AdaBoost Classifier by Dirk-Jan Kroon

Weak threshold classifier boosted to strong Classifier with Adaboost (adaboost, boosting, classification)

[estimateclasstotal,model]=adaboost(mode,datafeatures,datac...

example.m

PLS regression or discriminant analysis, with leave-one-out cross-validation and prediction. by Cleiton Nunes

M-files for PLS, PLS-DA, with leave-one-out cross-validation and prediction (classification, chemometrics, partial least squares)

pls(x,y,vl,da)

plscv(x,y,vl,da)

plspred(x,model,y)

Similarity classifier by Pasi Luukka

Classifier based on similarity measure. (biotech, image processing, data exploration)

[Classification_accuracy,p1,m1,classes]=simclass(datalearn,...

[Mean_accuracy, Variance,p1,m1]=simclass2(data,v,c, measure...

calcfitness(data, ideals, y, w)

CLUSTERING THROUGH OPTIMAL BAYESIAN CLASSIFICATION by Lionel

The package contains function for performing soft clustering. (statistics, clustering, clusters)

Dis=contrastEM(x,centroids,py_x)

[npy_x,npy,idxClus]=distinctW(w,py_x,py)

[py_x,centroids,clustind,complexity]=EM(x,beta,varargin)

Chemometric data preprocessing by Cleiton Nunes

M-files for data preprocessing by several methods. (chemometrics, calibration, preprocessing)

[x_msc]=msc(x,xref)

abstrans(X)

auto(x)

Demos from "Computer Vision with MATLAB" webinar by Bruce Tannenbaum

Demo files for the "Computer Vision with MATLAB" webinar held on April 19, 2011. (computer vision, video processing, image processing)

FeatureBasedRegistration.m

StereoDisparityMap.m

TextureClassification.m

Feature selection using fuzzy entropy measures and similarity by Pasi Luukka

Removes a feature from data file which it considers havining least amount of relevant information. (data exploration, measurement, biotech)

[data_mod, index_rem]=feat_sel_sim(data, measure, p)

Estatística Computacional: Introdução a Classificação de Padrões utilizando o MATLAB by Elia Matsumoto

Slides and demo files from the live webinar. (webinar, live webinar, matlab)

WhiteWine.m

Discretization algorithms: Class-Attribute Contingency Coefficient by Guangdi Li

To discrete continuous data, CACC is a promising discretization scheme proposed in 2008 (discretization, data mining, classification)

CACC_Discretization( OriginalData, C )

ControlCenter.m

GUI for Multivariate Image Analysis of 4-dimensional data by Kateryna Artyushkova

Multivariate Image Analysis of 4-dimensional image sequences using 2-step two-way and three-way ... (pca, simplisma, image analysis)

[Classes,Centres,FinalDistance]=dcKMeans(Data,k,InitCentres...

[M,mask]=profile_z(images);

[c,t]=trilin(c,ne,ishape)

CAIM Discretization Algorithm by Guangdi Li

CAIM (class-attribute interdependence maximization) is designed to discretize continuous data. (discretization, classification, data mining)

CAIM_Discretization( OriginalData, C )

CAIM_Evaluation( OriginalData, C, Feature, DiscretInterval ...

DiscretWithInterval( OriginalData,C,Column,DiscretInterval ...

class_vectors by Dr.Rajen Bhatt

Generates classification vectors to be used with any winner-takes-all classifiers. (classification, data exploration)

V=class_vectors(Y)

Introduction to Classification by Richard Willey

Files and code from Computational Statistics: Getting Started with Classification using MATLAB® (classification, machine learning, naive bayes)

WhiteWine.m

Radon-Like Features by Ritwik Kumar

Radon-Like Features can be used for image segmentation and classification. (image processing, segmentation, classification)

F=makeBarFilters(sup, or, sc)

getEdgeFeatures(im, sup, sc, or)

radonLikeFeaturesDemo.m

Rosenblatt's Perceptron by Ibraheem Al-Dhamari

A very simple Neural Networks example. (classification, svm, perceptron)

MyPerecptronExample

[w,b,pass]=PerecptronTrn(x,y);

e=PerecptronTst(x,y,w,b);

Max Margin Ratio Machine by Suicheng Gu

The Code for max margin ratio machine (large margin, kernel machine, support vectors)

kmrtrain ( Y , X , t , g , theta )

kpredict ( Y , X , model )

simple_usps.m

PCA based face recognition by Gholamreza (Shahab) Anbarjafari

This code is PCA base face recognition programme. (classification, face recognition, pca)

PCA_Face_Recognition.m

Precision-Recall and ROC Curves by Stefan Schroedl

Calculate and plot P/R and ROC curves for binary classification tasks. (precision recall curv..., classification, precisionrecall curve)

prec_rec(score, target, varargin)

Blind recognition of space time codes by Choqueuse Vincent

These scripts implement several algorithms for the blind recognition of space time block codes. (mimo, stbc, space time block code)

PermsRep(v,k)

[]=Blind_recognition_STBC2_simulation_results(N,nr,Modulati...

[]=Blind_recognition_STBC4_simulation_results(N,nr,Modulati...

DeltaRule by Will Dwinnell

Trains a single artificial neuron using the delta rule. (neural, neural net, neural network)

DeltaRule(X,Y,LearningRate,MinimumWeightChange,MaximumPasse...

Logistic(Input)

Basic PCA based log-Likelihood Classifier by Dirk-Jan Kroon

PCA algorithm suitable for detection / recognition of 2D image "objects" (classification, recognition, likelihood)

[Lmean,Gmean,Cgppca,invCgppca,Vtot]=train_model(L,G)

[distanceL,distanceG,LogLikelihood]=apply_model(T,Lmean,Gme...

example_classifier_ms.m

Applying Multivariate Classification in the Life Sciences with Statistics Toolbox by Sam Roberts

Files from the webinar "Multivariate Classification in the Life Sciences with Statistics Toolbox" (biotech, statistics, life science)

Prediction of tumor class from gene expression data using b...

gaussian_mixture_model.m by Matthew Roughan

Estimate the parameters of a 1D Gaussian Mixture Model using the EM algorithm. (expectation maximizat..., estimation, em)

...

norm_density(x, mu, sigma)

normcdf(x, mu, sigma)

Compressive Classifier by Angshul Majumdar

Classifiers Robust to Dimensionality Reduction via Random Projections (classification, optimization, signal processing)

FGSC(Train, Test, cs, repeat, type)

FSC(Train, Test, cs, repeat, type)

GSC(Train, Test, cs, repeat, type)

Principal Component Analysis (PCA) in MATLAB by Siamak Faridani

This is a demonstration of how one can use PCA to classify a 2D data set. (pca, classification, principal component a...)

pca.m

Discriminant Analysis Programme by Bartolomeu Rabacal

Discrimination and Classification of data to and from groups with classical/robust estimation (statistics, classification, discrimination)

DAP(varargin)

DSEst.m

DSWeightings(directions, DSParm)

Fuzzy k-NN by Cuneyt Mertayak

Fuzzy k-nearest neighbors classifier that was proposed by J. M. Keller et.al. (statistics, probability, fuzzy)

f_knn(tr,tr_memberships,te,k)

AdaBoost by Cuneyt Mertayak

AdaBoost: The meta machine learning algorithm formulated by Yoav Freund and Robert Schapire (adaboost, adaptive boosting, classification)

ADABOOST_te(adaboost_model,te_func_handle,test_set,...

ADABOOST_tr(tr_func_handle, te_func_handle, train_set, labe...

likelihood2class(likelihoods)

Introduction to Object-Oriented Programming in MATLAB by Linda Webb

Use of object-oriented techniques in the MATLAB language to implement typical technical application (whitepaper, article, paper)

Linear matrix-based neural network by Povilas Daniu?is

A novel learning algorithm for matrix-based data (fuzzy logic, neural networks, small sample)

[u,v]=nMatReg(X,y,M,N,lambda)

AUROC - Area under Receiver Operating Characteristic by Stefan Schroedl

Compute AUROC from frequency weighted instances of predictions and ratio of positive instances (statistics, probability, auroc)

aucroc(p_predicted, p_target, freq)