Code covered by the BSD License
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Cont=Contingency(Mem1,Mem2)
CONTINGENCY Form contigency matrix for two vectors
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DCAgg(Distance, Method, k)
DCAGG Performs agglomerative clustering
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LogFactorial(n)
LOGFACTORIAL Calculates the Natural log of the factorial of n
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MakeGaussData(NCentres,NDims,...
MAKEGAUSSDATA - Creates spherical data clouds
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MaxMax(x)
MAXMAX Maximum of all elements in an n-dimension array
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MeanMean(x)
MEANMEAN Mean of all elements in an n-dimension array
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MinMin(x)
MINMIN Minimum of all elements in an n-dimension array
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PCAGraph(X,dims,labels)
PCAGRAPH Plots data projected onto its first 2 principal components
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SumSum(x)
SUMSUM Sums all elements in an n-dimension array
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[AR,RI,MI,HI]=RandIndex(c1,c2...
RANDINDEX - calculates Rand Indices to compare two partitions
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[C,perm]=ChooseInitialCentres...
CHOOSEINITIALCENTRES Randomly picks sample points
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[Classes,Centres,FinalDistanc...
DCKMEANS Performs k-means clustering
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[RITrue,RISelf,EstIndex]=DoCl...
DOCLUSTERING Performs cluster analysis of specified data using specified
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[mix, class,likelihood]=dcEMG...
DCEMGMM - estimates Gaussian Mixture Model using the EM algorithm
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[purspec,purint,purity_spec]=...
function [purspec,purint,purity_spec]=simplisma(data,varlist,offset,n,data2);
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array_subset=array_downsizing...
function array_subset=array_downsizing(array, N);
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c=PlotColour(index,lineflag)
PLOTCOLOUR Returns colour and marker string for PLOT
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class=im_class_MLE(im,plot);
function class=im_class_MLE(im,plot);
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data_der=invder(data)
data_der=invder(data)
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dcFuzzy(X,c,m,InitCentres)
DCFUZZY Performs fuzzy c-means clustering
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histogram(varargin)
GUI for Plotting historgam and equalizing image arrays
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im=vms_im_read(filename,plot)...
im=vms_im_read(filename,plot);
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image_mva(varargin)
GUI for Multivariate Analysis of images
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profiles(varargin)
GUI for plotting profiles for image arrays
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threshold(varargin)
GUI for thresholding images
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threshold_grayscale_image(ori...
431-400 Year Long Project
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Contents.m
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DcDemo.m
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uigetfiles.m
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View all files
from
GUI for Multivariate Image Analysis of Multispectral Images
by Kateryna Artyushkova
A GUI for MIA of multispectral image data sets (PCA, Simplisma, MCR, classification).
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| Contents.m |
% Clustering Toolbox
% Copyright (C) David Corney 2000 D.Corney@cs.ucl.ac.uk
%
%Clustering routines:
%
% dckmeans - k-means clustering
% dcEMGMM - fits a Gaussian mixture model to data
% dcFuzzy - fuzzy c-means clustering
% dcAgg - agglomerative (hierarchical) clustering
% DoClustering - call the above routines
%
%
%Utilities:
% ChooseInitialCentres - chooses k points from set
% Contingency - forms contingency matrix
% LogFactorial - calculates log of factorial
% MakeGaussData - creates spherical Gaussian data sets
% MaxMax - max value in n-d array
% MeanMean - mean value in n-d array
% MinMin - min value in n-d array
% PCAGraph - plots graph using first 2/3 principal components
% PlotColour - returns string for PLOT marker (colour,shape)
% RandIndex - calculates adjusted Rand index for cluster solutions
% SumSum - sum value in n-d array
%
%Plus:
% DcDemo - simple script demonstrating some of these functions
%
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