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updated 1 month ago

Spatial-Spectral Dimensionality Reduction with Partial Knowledge of Class Labels by Nathan Cahill

Semi-supervised graph-based dimensionality reduction for hyperspectral image data (dimensionality reduct..., laplacian eigenmaps, schroedinger eigenmap...)

adjacencyMatrixBenedetto(varargin)

adjacencyMatrixGillisBowles(varargin)

adjacencyMatrixHZYZ(varargin)

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updated 1 month ago

SLIC Superpixels for Eļ¬ƒcient Graph-Based Dimensionality Reduction of Hyperspectral Imagery by Nathan Cahill

Improving graph-based dimensionality reduction techniques for image data to incorporate superpixels (superpixels, dimensionality reduct..., laplacian eigenmaps)

adjacencyMatrixGillisBowlesSuperpixels(varargin)

adjacencyMatrixHZYZSuperpixels(varargin)

adjacencyMatrixShiMalikSuperpixels(varargin)

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updated 2 months ago

Discriminant Diffusion Maps Analysis by David Huang

Demo of discriminant diffusion maps analysis (DDMA) on a 3D three-arm spiral data set (feature fusion, manifold learning, diffusion maps)

ddma(dat, lab, neigen, gamma, t, neighbor)

demo.m

gen_spir_3d.m

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updated 5 months ago

GPLVM-WPHM by James Barrett

Dimensionality reduction tool for survival (time-to-event) data. (survival analysis, gplvm, dimensionality reduct...)

gw_hyp(p, initial_x, b_wc, model)

gw_initialise(gw_options, t, E, varargin)

gw_multiple_train(gw_options_multiple, q, t, E, varargin)

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updated 9 months ago

Spatial-Spectral Schroedinger Eigenmaps by Nathan Cahill

Graph-based dimensionality reduction technique for image data (schroedinger eigenmap..., laplacian eigenmaps, dimensionality reduct...)

adjacencyMatrix(varargin)

createTrainTestData(gtLabels,trainPrct)

schroedingerEigenmap(L,V,beta,numEigs)

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updated 10 months ago

Graph-based clustering and data visualization algorithms by Janos Abonyi

Janos Abonyi (view profile)

Combines graph-based topology representation and dimensionality reduction methods (graph, visualization, dimensionality reduct...)

L2_distance(a,b,df)

MDS(D, options);

[Fpn conn]=jarpat(X,k,j,tr1)

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updated 11 months ago

Low Rank Multivariate Autoregressive Model for Dimensionality Reduction by Diego Vidaurre

Dimensionality reduction approach for time series data based on multivariate autoregressive models (dimensionality reduct..., autoregressive models, mar)

[model,Z,fehist]=lrmartrain(X,options)

evalfreeenergy (X,model,Z)

gamma_kl (shape_q,shape_p,rate_q,rate_p)

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updated 1 year ago

Uncorrelated Multilinear Discriminant Analysis (UMLDA) by Haiping Lu

Haiping Lu (view profile)

The codes implement the Uncorrelated Multilinear Discriminant Analysis (UMLDA) algorithm. (dimensionality reduct..., face recognition, feature extraction)

CombR1s=calcR1(allnewfeas,gnd,trainIdx,testIdx)

MaxSWLmds=estMaxSWEV(TX,gndTX)

RUMLDA(TX,gndTX,numP,gamma,MaxSWLmds,iInit)

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updated almost 3 years ago

Multilinear Principal Component Analysis (MPCA) by Haiping Lu

Haiping Lu (view profile)

The codes implement two algorithms: Multilinear Principal Component Analysis (MPCA) and MPCA+LDA. (image processing, video processing, dimensionality reduct...)

MPCA(TX,gndTX,testQ,maxK)

MPCALDA(TX,gndTX,MPCADADim,testQ,maxK)

[GaitDBDir,probes,numprobe]=testData

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updated 3 years ago

Uncorrelated Multilinear Principal Component Analysis (UMPCA) by Haiping Lu

Haiping Lu (view profile)

The codes implement the Uncorrelated Multilinear Principal Component Analysis (UMPCA) algorithm. (dimensionality reduct..., feature extraction, image processing)

UMPCA(TX,numP)

maxeig(A)

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updated 3 years ago

The PhD face recognition toolbox by Vitomir Struc

Vitomir Struc (view profile)

Useful functions for face recognition research. (face recognition, image processing, biometrics)

compute_kernel_matrix_PhD.m

construct_Gabor_filters_PhD.m

evaluate_results_PhD.m

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updated 5 years ago

MANCOVAN by William Gruner

Tools for Multivariate Analysis (Statistics Toolbox NOT Required) (anova, ancova, anovan)

mC2X(covariates, offset, options, columns)

mCC2X(covariates, offset, options, columns)

mDemoA

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