y=[1:10]; mycell = cell(10,1); for i=1:5 mycell(i)=cellstr('mRNA prom'); end for i=6:10 mycell(i)=cellstr('lncRNA prom'); end boxplot(y , mycell ,'notch','on','whisker',1);
Install R in linux ============ In CRAN home page, the latest version is not available. So, in fedora, Open the terminal yum list R --> To check the latest available version of r yum install R --> install R version yum update R --> update current version to latest one 0 find help ============ ?exact topic name ( i.e. ?mean ) 0.0 INSTALL 3rd party package ==================== install.packages('mvtnorm' , dependencies = TRUE , lib='/home/alamt/myRlibrary/') # install new package BED file parsing (Always use read.delim it is the best) library(MASS) #library(ggplot2) dirRoot="D:/research/F5shortRNA/TestRIKEN/Rscripts/" dirData="D:/research/F5shortRNA/TestRIKEN/" setwd(dirRoot) getwd() myBed="test.bed" fnmBed=paste(dirData, myBed, sep="") # ccdsHh19.bed tmp.bed ## Read bed use read.delim - it is the best mybed=read.delim(fnmBed, header = FALSE, sep = "\t", quote = ...
// use built-in function samplesize = size( matrix , 1); c = cvpartition(samplesize, 'kfold' , k); % return the indexes on each fold ///// output in matlab console K-fold cross validation partition N: 10 NumTestSets: 4 TrainSize: 8 7 7 8 TestSize: 2 3 3 2 ////////////////////// for i=1 : k trainIdxs = find(training(c,i) ); %training(c,i); // 1 means in train , 0 means in test testInxs = find(test(c,i) ); % test(c,i); // 1 means in test , 0 means in train trainMatrix = matrix ( matrix(trainIdxs ), : ); testMatrix = matrix ( matrix(testIdxs ), : ); end //// now calculate performance %% calculate performance of a partiti...
Useful tutorial http://www.mathworks.com/products/global-optimization/description3.html Best example of implementatoin with Constraint, objective function http://www.mathworks.com/help/gads/examples/constrained-minimization-using-the-genetic-algorithm.html More about how to use multi-objective http://www.mathworks.com/discovery/multiobjective-optimization.html http://www.mathworks.com/help/gads/examples/performing-a-multiobjective-optimization-using-the-genetic-algorithm.html http://www.mathworks.com/help/gads/examples/multiobjective-genetic-algorithm-options.html Example GAMULTOBJ (can handle Multiple Objective) GA(can handle 1 objective) Constrained Minimization Problem We want to minimize a simple fitness function of two variables x1 and x2 min f(x) = 100 * (x1^2 - x2) ^2 + (1 - x1)^2; x min f(x) = 100 * (x1^2 + x2) ^2 + (1 + x1)^2; x such that the following two nonlinear constraints and bounds are satisfied x1*x2 + x1 - x2 + 1.5 <...
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