plateform stringclasses 1
value | repo_name stringlengths 13 113 | name stringlengths 3 74 | ext stringclasses 1
value | path stringlengths 12 229 | size int64 23 843k | source_encoding stringclasses 9
values | md5 stringlengths 32 32 | text stringlengths 23 843k |
|---|---|---|---|---|---|---|---|---|
github | xenron/sandbox-da-matlab-master | recmut.m | .m | sandbox-da-matlab-master/book/MATLAB神经网络43个案例分析/chapter20/libsvm-3.1-[FarutoUltimate3.1Mcode]/matlab-implement[by faruto]/myprivate/gatbx[Sheffield]/recmut.m | 4,735 | utf_8 | e7037b945697583b7b681ae93ef56665 | % RECLIN.M (line RECombination with MUTation features)
%
% This function performs line recombination with mutation features between
% pairs of individuals and returns the new individuals after mating.
%
% Syntax: NewChrom = recmut(OldChrom, FieldDR, MutOpt)
%
% Input parameters:
% OldChrom - Matrix containin... |
github | xenron/sandbox-da-matlab-master | xovsprs.m | .m | sandbox-da-matlab-master/book/MATLAB神经网络43个案例分析/chapter20/libsvm-3.1-[FarutoUltimate3.1Mcode]/matlab-implement[by faruto]/myprivate/gatbx[Sheffield]/xovsprs.m | 1,059 | utf_8 | bd0059a9b0685fb0d25ad669c7de984e | % XOVSPRS.M (CROSSOVer Single-Point with Reduced Surrogate)
%
% This function performs single-point 'reduced surrogate' crossover between
% pairs of individuals and returns the current generation after mating.
%
% Syntax: NewChrom = xovsprs(OldChrom, XOVR)
%
% Input parameters:
% OldChrom - Matrix containing... |
github | xenron/sandbox-da-matlab-master | scaling.m | .m | sandbox-da-matlab-master/book/MATLAB神经网络43个案例分析/chapter20/libsvm-3.1-[FarutoUltimate3.1Mcode]/matlab-implement[by faruto]/myprivate/gatbx[Sheffield]/scaling.m | 1,219 | utf_8 | d8872170a387a6e841955b0efd3456e1 | % SCALING.m - linear fitness scaling
%
% This function implements a linear fitness scaling algorithm as described
% by Goldberg in "Genetic Algorithms in Search, Optimization and Machine
% Learning", Addison Wesley, 1989. It use is not recommended when fitness
% functions produce negative results as the scaling will b... |
github | xenron/sandbox-da-matlab-master | crtrp.m | .m | sandbox-da-matlab-master/book/MATLAB神经网络43个案例分析/chapter20/libsvm-3.1-[FarutoUltimate3.1Mcode]/matlab-implement[by faruto]/myprivate/gatbx[Sheffield]/crtrp.m | 2,039 | utf_8 | 1c83222a36bb7c88e41346cac82d549d | % CRTRP.M (CReaTe an initial (Real-value) Population)
%
% This function creates a population of given size of random real-values.
%
% Syntax: Chrom = crtrp(Nind,FieldDR);
%
% Input parameters:
% Nind - A scalar containing the number of individuals in the new
% population.
%
% Fi... |
github | xenron/sandbox-da-matlab-master | crtbp.m | .m | sandbox-da-matlab-master/book/MATLAB神经网络43个案例分析/chapter20/libsvm-3.1-[FarutoUltimate3.1Mcode]/matlab-implement[by faruto]/myprivate/gatbx[Sheffield]/crtbp.m | 2,116 | utf_8 | 0262d6199e6215c6de17ffcdd480c09e | % CRTP.m - Create an initial population
%
% This function creates a binary population of given size and structure.
%
% Syntax: [Chrom Lind BaseV] = crtbp(Nind, Lind, Base)
%
% Input Parameters:
%
% Nind - Either a scalar containing the number of individuals
% in the new population or a row vector of length two
% ... |
github | xenron/sandbox-da-matlab-master | rep.m | .m | sandbox-da-matlab-master/book/MATLAB神经网络43个案例分析/chapter20/libsvm-3.1-[FarutoUltimate3.1Mcode]/matlab-implement[by faruto]/myprivate/gatbx[Sheffield]/rep.m | 1,163 | utf_8 | 522fc66ca0b4d8c634ff478c54fc3174 | % REP.m Replicate a matrix
%
% This function replicates a matrix in both dimensions.
%
% Syntax: MatOut = rep(MatIn,REPN);
%
% Input parameters:
% MatIn - Input Matrix (before replicating)
%
% REPN - Vector of 2 numbers, how many replications in each dimension
% REPN(1): replicate... |
github | xenron/sandbox-da-matlab-master | rws.m | .m | sandbox-da-matlab-master/book/MATLAB神经网络43个案例分析/chapter20/libsvm-3.1-[FarutoUltimate3.1Mcode]/matlab-implement[by faruto]/myprivate/gatbx[Sheffield]/rws.m | 1,060 | utf_8 | 3e57371be37c2afe31e534bacac38ef1 | % RWS.m - Roulette Wheel Selection
%
% Syntax:
% NewChrIx = rws(FitnV, Nsel)
%
% This function selects a given number of individuals Nsel from a
% population. FitnV is a column vector containing the fitness
% values of the individuals in the population.
%
% The function retur... |
github | xenron/sandbox-da-matlab-master | recint.m | .m | sandbox-da-matlab-master/book/MATLAB神经网络43个案例分析/chapter20/libsvm-3.1-[FarutoUltimate3.1Mcode]/matlab-implement[by faruto]/myprivate/gatbx[Sheffield]/recint.m | 1,841 | utf_8 | 2e2ce4e7253b27b11965de41bbb06e97 | % RECINT.M (RECombination extended INTermediate)
%
% This function performs extended intermediate recombination between
% pairs of individuals and returns the new individuals after mating.
%
% Syntax: NewChrom = recint(OldChrom, XOVR)
%
% Input parameters:
% OldChrom - Matrix containing the chromosomes of th... |
github | xenron/sandbox-da-matlab-master | xovdp.m | .m | sandbox-da-matlab-master/book/MATLAB神经网络43个案例分析/chapter20/libsvm-3.1-[FarutoUltimate3.1Mcode]/matlab-implement[by faruto]/myprivate/gatbx[Sheffield]/xovdp.m | 1,011 | utf_8 | 307a96a23a58ae75230f93ac3305abdd | % XOVDP.M (CROSSOVer Double Point)
%
% This function performs double point crossover between pairs of
% individuals and returns the current generation after mating.
%
% Syntax: NewChrom = xovdp(OldChrom, XOVR)
%
% Input parameters:
% OldChrom - Matrix containing the chromosomes of the old
% p... |
github | xenron/sandbox-da-matlab-master | resplot.m | .m | sandbox-da-matlab-master/book/MATLAB神经网络43个案例分析/chapter20/libsvm-3.1-[FarutoUltimate3.1Mcode]/matlab-implement[by faruto]/myprivate/gatbx[Sheffield]/resplot.m | 2,025 | utf_8 | 0f9e36690c2696ad8733a25ca62f6e66 | % RESPLOT.M (RESult PLOTing)
%
% This function plots some results during computation.
%
% Syntax: resplot(Chrom,IndAll,ObjV,Best,gen)
%
% Input parameters:
% Chrom - Matrix containing the chromosomes of the current
% population. Each line corresponds to one individual.
% IndAll - Matr... |
github | xenron/sandbox-da-matlab-master | mutbga.m | .m | sandbox-da-matlab-master/book/MATLAB神经网络43个案例分析/chapter20/libsvm-3.1-[FarutoUltimate3.1Mcode]/matlab-implement[by faruto]/myprivate/gatbx[Sheffield]/mutbga.m | 4,831 | utf_8 | 798dcff17df5007819ffccc1692be180 | % MUTBGA.M (real-value MUTation like Breeder Genetic Algorithm)
%
% This function takes a matrix OldChrom containing the real
% representation of the individuals in the current population,
% mutates the individuals with probability MutR and returns
% the resulting population.
%
% This function implements the muta... |
github | xenron/sandbox-da-matlab-master | xovdprs.m | .m | sandbox-da-matlab-master/book/MATLAB神经网络43个案例分析/chapter20/libsvm-3.1-[FarutoUltimate3.1Mcode]/matlab-implement[by faruto]/myprivate/gatbx[Sheffield]/xovdprs.m | 1,059 | utf_8 | 1a80762a7f575ac6f9b3814857714a63 | % XOVDPRS.M (CROSSOVer Double-Point with Reduced Surrogate)
%
% This function performs double-point 'reduced surrogate' crossover between
% pairs of individuals and returns the current generation after mating.
%
% Syntax: NewChrom = xovdprs(OldChrom, XOVR)
%
% Input parameters:
% OldChrom - Matrix containing... |
github | xenron/sandbox-da-matlab-master | mutate.m | .m | sandbox-da-matlab-master/book/MATLAB神经网络43个案例分析/chapter20/libsvm-3.1-[FarutoUltimate3.1Mcode]/matlab-implement[by faruto]/myprivate/gatbx[Sheffield]/mutate.m | 3,356 | utf_8 | 76b01fbb1235eaa8ad0d2b8e6c202e52 | % MUTATE.M (MUTATion high-level function)
%
% This function takes a matrix OldChrom containing the
% representation of the individuals in the current population,
% mutates the individuals and returns the resulting population.
%
% The function handles multiple populations and calls the low-level
% mutation functi... |
github | xenron/sandbox-da-matlab-master | crtbase.m | .m | sandbox-da-matlab-master/book/MATLAB神经网络43个案例分析/chapter20/libsvm-3.1-[FarutoUltimate3.1Mcode]/matlab-implement[by faruto]/myprivate/gatbx[Sheffield]/crtbase.m | 1,122 | utf_8 | 4992ebac5f7aa555598ac6fb56477894 | % CRTBASE.m - Create base vector
%
% This function creates a vector containing the base of the loci
% in a chromosome.
%
% Syntax: BaseVec = crtbase(Lind, Base)
%
% Input Parameters:
%
% Lind - A scalar or vector containing the lengths
% of the alleles. Sum(Lind) is the length of
% the corresponding chromoso... |
github | xenron/sandbox-da-matlab-master | xovsh.m | .m | sandbox-da-matlab-master/book/MATLAB神经网络43个案例分析/chapter20/libsvm-3.1-[FarutoUltimate3.1Mcode]/matlab-implement[by faruto]/myprivate/gatbx[Sheffield]/xovsh.m | 1,001 | utf_8 | 8351ff203d7566d23a533028f1fc42d2 | % XOVSH.M (CROSSOVer SHuffle)
%
% This function performs shuffle crossover between pairs of
% individuals and returns the current generation after mating.
%
% Syntax: NewChrom = xovsh(OldChrom, XOVR)
%
% Input parameters:
% OldChrom - Matrix containing the chromosomes of the old
% population.... |
github | xenron/sandbox-da-matlab-master | reclin.m | .m | sandbox-da-matlab-master/book/MATLAB神经网络43个案例分析/chapter20/libsvm-3.1-[FarutoUltimate3.1Mcode]/matlab-implement[by faruto]/myprivate/gatbx[Sheffield]/reclin.m | 1,897 | utf_8 | 1b854d6c172c3c64433646f4815e800b | % RECLIN.M (RECombination extended LINe)
%
% This function performs extended line recombination between
% pairs of individuals and returns the new individuals after mating.
%
% Syntax: NewChrom = reclin(OldChrom, XOVR)
%
% Input parameters:
% OldChrom - Matrix containing the chromosomes of the old
% ... |
github | xenron/sandbox-da-matlab-master | xovmp.m | .m | sandbox-da-matlab-master/book/MATLAB神经网络43个案例分析/chapter20/libsvm-3.1-[FarutoUltimate3.1Mcode]/matlab-implement[by faruto]/myprivate/gatbx[Sheffield]/xovmp.m | 2,712 | utf_8 | 2fcf985e764ebd2f8abf1c4efc9d9b44 | % XOVMP.m Multi-point crossover
%
% Syntax: NewChrom = xovmp(OldChrom, Px, Npt, Rs)
%
% This function takes a matrix OldChrom containing the binary
% representation of the individuals in the current population,
% applies crossover to consecutive pairs of individuals with
% ... |
github | xenron/sandbox-da-matlab-master | xovsp.m | .m | sandbox-da-matlab-master/book/MATLAB神经网络43个案例分析/chapter20/libsvm-3.1-[FarutoUltimate3.1Mcode]/matlab-implement[by faruto]/myprivate/gatbx[Sheffield]/xovsp.m | 1,012 | utf_8 | 930745320d1d2c50db84573794038686 | % XOVSP.M (CROSSOVer Single-Point)
%
% This function performs single-point crossover between pairs of
% individuals and returns the current generation after mating.
%
% Syntax: NewChrom = xovsp(OldChrom, XOVR)
%
% Input parameters:
% OldChrom - Matrix containing the chromosomes of the old
% ... |
github | xenron/sandbox-da-matlab-master | regRF_predict.m | .m | sandbox-da-matlab-master/book/MATLAB神经网络43个案例分析/chapter30/RF_MexStandalone-v0.02/randomforest-matlab/RF_Reg_C/regRF_predict.m | 986 | utf_8 | 12601a7e5a27c8772b59437808384bbe | %**************************************************************
%* mex interface to Andy Liaw et al.'s C code (used in R package randomForest)
%* Added by Abhishek Jaiantilal ( abhishek.jaiantilal@colorado.edu )
%* License: GPLv2
%* Version: 0.02
%
% Calls Regression Random Forest
% A wrapper matlab file that calls the... |
github | xenron/sandbox-da-matlab-master | regRF_train.m | .m | sandbox-da-matlab-master/book/MATLAB神经网络43个案例分析/chapter30/RF_MexStandalone-v0.02/randomforest-matlab/RF_Reg_C/regRF_train.m | 12,863 | utf_8 | a9c73de9b026cf655cbb18496e685f8c | %**************************************************************
%* mex interface to Andy Liaw et al.'s C code (used in R package randomForest)
%* Added by Abhishek Jaiantilal ( abhishek.jaiantilal@colorado.edu )
%* License: GPLv2
%* Version: 0.02
%
% Calls Regression Random Forest
% A wrapper matlab file that calls th... |
github | xenron/sandbox-da-matlab-master | compile_windows.m | .m | sandbox-da-matlab-master/book/MATLAB神经网络43个案例分析/chapter30/RF_MexStandalone-v0.02/randomforest-matlab/RF_Reg_C/compile_windows.m | 801 | utf_8 | 1a638f868f9498ca3a5f980c4a5a03e7 | % ********************************************************************
% * mex File compiling code for Random Forest (for windows)
% * mex interface to Andy Liaw et al.'s C code (used in R package randomForest)
% * Added by Abhishek Jaiantilal ( abhishek.jaiantilal@colorado.edu )
% * License: GPLv2
% * Version: 0.02
% ... |
github | xenron/sandbox-da-matlab-master | compile_linux.m | .m | sandbox-da-matlab-master/book/MATLAB神经网络43个案例分析/chapter30/RF_MexStandalone-v0.02/randomforest-matlab/RF_Reg_C/compile_linux.m | 952 | utf_8 | 69f27cce34b27de861e600f366e71001 | % ********************************************************************
% * mex File compiling code for Random Forest (for linux)
% * mex interface to Andy Liaw et al.'s C code (used in R package randomForest)
% * Added by Abhishek Jaiantilal ( abhishek.jaiantilal@colorado.edu )
% * License: GPLv2
% * Version: 0.02
% *... |
github | xenron/sandbox-da-matlab-master | classRF_predict.m | .m | sandbox-da-matlab-master/book/MATLAB神经网络43个案例分析/chapter30/RF_MexStandalone-v0.02/randomforest-matlab/RF_Class_C/classRF_predict.m | 2,166 | utf_8 | 7e026fb9b31f99feae58d36b9cf6c2e0 | %**************************************************************
%* mex interface to Andy Liaw et al.'s C code (used in R package randomForest)
%* Added by Abhishek Jaiantilal ( abhishek.jaiantilal@colorado.edu )
%* License: GPLv2
%* Version: 0.02
%
% Calls Classification Random Forest
% A wrapper matlab file that calls... |
github | xenron/sandbox-da-matlab-master | compile_windows.m | .m | sandbox-da-matlab-master/book/MATLAB神经网络43个案例分析/chapter30/RF_MexStandalone-v0.02/randomforest-matlab/RF_Class_C/compile_windows.m | 1,589 | utf_8 | dace2fcb13032c76c27364b1a5b24a33 | % ********************************************************************
% * mex File compiling code for Random Forest (for linux)
% * mex interface to Andy Liaw et al.'s C code (used in R package randomForest)
% * Added by Abhishek Jaiantilal ( abhishek.jaiantilal@colorado.edu )
% * License: GPLv2
% * Version: 0.02
% **... |
github | xenron/sandbox-da-matlab-master | classRF_train.m | .m | sandbox-da-matlab-master/book/MATLAB神经网络43个案例分析/chapter30/RF_MexStandalone-v0.02/randomforest-matlab/RF_Class_C/classRF_train.m | 14,829 | utf_8 | 82a321d0a7c77f33b104acec4394c6ee | %**************************************************************
%* mex interface to Andy Liaw et al.'s C code (used in R package randomForest)
%* Added by Abhishek Jaiantilal ( abhishek.jaiantilal@colorado.edu )
%* License: GPLv2
%* Version: 0.02
%
% Calls Classification Random Forest
% A wrapper matlab file that calls... |
github | xenron/sandbox-da-matlab-master | compile_linux.m | .m | sandbox-da-matlab-master/book/MATLAB神经网络43个案例分析/chapter30/RF_MexStandalone-v0.02/randomforest-matlab/RF_Class_C/compile_linux.m | 557 | utf_8 | c21b7b493153f2254a8a2c4d7be848f1 | % ********************************************************************
% * mex File compiling code for Random Forest (for linux)
% * mex interface to Andy Liaw et al.'s C code (used in R package randomForest)
% * Added by Abhishek Jaiantilal ( abhishek.jaiantilal@colorado.edu )
% * License: GPLv2
% * Version: 0.02
% **... |
github | xenron/sandbox-da-matlab-master | plotroc.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_6_Code/libsvm-mat-2[1].89-3[FarutoUltimate3.0Mcode]/implement[by faruto]/myprivate/plotroc.m | 5,369 | utf_8 | 5e1408e4b158818915bf2d4fb2c15f57 | function result = plotroc(varargin)
%PLOTROC Plot receiver operating characteristic.
%
% Syntax
%
% plotroc(targets,outputs)
% plotroc(targets1,outputs1,'name1',targets,outputs2,'name2', ...)
%
% Description
%
% PLOTROC(TARGETS,OUTPUTS) plots the receiver operating characteristic
% for each output class. ... |
github | xenron/sandbox-da-matlab-master | roc.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_6_Code/libsvm-mat-2[1].89-3[FarutoUltimate3.0Mcode]/implement[by faruto]/myprivate/roc.m | 4,132 | utf_8 | 6130bd3e03a216a01c34b26668dca067 | function [tpr,fpr,thresholds] = roc(targets,outputs)
%ROC Receiver operating characteristic.
%
% Syntax
%
% [tpr,fpr,thresholds] = roc(targets,outputs)
%
% Description
%
% The receiver operating characteristic is a metric used to check
% the quality of classifiers. For each class of a classifier,
% thresh... |
github | xenron/sandbox-da-matlab-master | mapminmax_new.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_6_Code/libsvm-mat-2[1].89-3[FarutoUltimate3.0Mcode]/implement[by faruto]/myprivate/mapminmax_new.m | 5,545 | utf_8 | 3882777434d91dd7ff3a71dea68fc39c | function [out1,out2] = mapminmax(in1,in2,in3,in4)
%MAPMINMAX Map matrix row minimum and maximum values to [-1 1].
%
% Syntax
%
% [y,ps] = mapminmax(x,ymin,ymax)
% [y,ps] = mapminmax(x,fp)
% y = mapminmax('apply',x,ps)
% x = mapminmax('reverse',y,ps)
% dx_dy = mapminmax('dx',x,y,ps)
% dx_dy = mapminmax('d... |
github | xenron/sandbox-da-matlab-master | recdis.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_6_Code/libsvm-mat-2[1].89-3[FarutoUltimate3.0Mcode]/implement[by faruto]/myprivate/gatbx[Sheffield]/recdis.m | 1,774 | utf_8 | caa65c1f80c486b258f0b787c741bf9a | % RECDIS.M (RECombination DIScrete)
%
% This function performs discret recombination between pairs of individuals
% and returns the new individuals after mating.
%
% Syntax: NewChrom = recdis(OldChrom, XOVR)
%
% Input parameters:
% OldChrom - Matrix containing the chromosomes of the old
% popu... |
github | xenron/sandbox-da-matlab-master | select.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_6_Code/libsvm-mat-2[1].89-3[FarutoUltimate3.0Mcode]/implement[by faruto]/myprivate/gatbx[Sheffield]/select.m | 2,333 | utf_8 | b47cd4eb63dac6daa67b0fde300452e0 | % SELECT.M (universal SELECTion)
%
% This function performs universal selection. The function handles
% multiple populations and calls the low level selection function
% for the actual selection process.
%
% Syntax: SelCh = select(SEL_F, Chrom, FitnV, GGAP, SUBPOP)
%
% Input parameters:
% SEL_F - Name... |
github | xenron/sandbox-da-matlab-master | xovshrs.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_6_Code/libsvm-mat-2[1].89-3[FarutoUltimate3.0Mcode]/implement[by faruto]/myprivate/gatbx[Sheffield]/xovshrs.m | 1,049 | utf_8 | f872954b60e93a8c59f4a3c1c7a6d74f | % XOVSHRS.M (CROSSOVer SHuffle with Reduced Surrogate)
%
% This function performs shuffle 'reduced surrogate' crossover between
% pairs of individuals and returns the current generation after mating.
%
% Syntax: NewChrom = xovshrs(OldChrom, XOVR)
%
% Input parameters:
% OldChrom - Matrix containing the chrom... |
github | xenron/sandbox-da-matlab-master | migrate.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_6_Code/libsvm-mat-2[1].89-3[FarutoUltimate3.0Mcode]/implement[by faruto]/myprivate/gatbx[Sheffield]/migrate.m | 7,057 | utf_8 | f5347623804b8e202b5799118f889682 | % MIGRATE.M (MIGRATion of individuals between subpopulations)
%
% This function performs migration of individuals.
%
% Syntax: [Chrom, ObjV] = migrate(Chrom, SUBPOP, MigOpt, ObjV)
%
% Input parameters:
% Chrom - Matrix containing the individuals of the current
% population. Each row correspo... |
github | xenron/sandbox-da-matlab-master | sus.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_6_Code/libsvm-mat-2[1].89-3[FarutoUltimate3.0Mcode]/implement[by faruto]/myprivate/gatbx[Sheffield]/sus.m | 1,279 | utf_8 | f2a8222f57502e1de92890f97377cae7 | % SUS.M (Stochastic Universal Sampling)
%
% This function performs selection with STOCHASTIC UNIVERSAL SAMPLING.
%
% Syntax: NewChrIx = sus(FitnV, Nsel)
%
% Input parameters:
% FitnV - Column vector containing the fitness values of the
% individuals in the population.
% Nsel - nu... |
github | xenron/sandbox-da-matlab-master | ranking.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_6_Code/libsvm-mat-2[1].89-3[FarutoUltimate3.0Mcode]/implement[by faruto]/myprivate/gatbx[Sheffield]/ranking.m | 4,585 | utf_8 | 764e33df698db260012d0c3d2f12cdeb | % RANKING.M (RANK-based fitness assignment)
%
% This function performs ranking of individuals.
%
% Syntax: FitnV = ranking(ObjV, RFun, SUBPOP)
%
% This function ranks individuals represented by their associated
% cost, to be *minimized*, and returns a column vector FitnV
% containing the corresponding individual ... |
github | xenron/sandbox-da-matlab-master | recombin.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_6_Code/libsvm-mat-2[1].89-3[FarutoUltimate3.0Mcode]/implement[by faruto]/myprivate/gatbx[Sheffield]/recombin.m | 2,370 | utf_8 | eb464a3e9c3ab4ee39fd8ba7314e6cfe | % RECOMBIN.M (RECOMBINation high-level function)
%
% This function performs recombination between pairs of individuals
% and returns the new individuals after mating. The function handles
% multiple populations and calls the low-level recombination function
% for the actual recombination process.
%
% Syntax: New... |
github | xenron/sandbox-da-matlab-master | bs2rv.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_6_Code/libsvm-mat-2[1].89-3[FarutoUltimate3.0Mcode]/implement[by faruto]/myprivate/gatbx[Sheffield]/bs2rv.m | 3,103 | utf_8 | dc467c5bc085074cdce377944607e359 | % BS2RV.m - Binary string to real vector
%
% This function decodes binary chromosomes into vectors of reals. The
% chromosomes are seen as the concatenation of binary strings of given
% length, and decoded into real numbers in a specified interval using
% either standard binary or Gray decoding.
%
% Syntax: Phen ... |
github | xenron/sandbox-da-matlab-master | reins.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_6_Code/libsvm-mat-2[1].89-3[FarutoUltimate3.0Mcode]/implement[by faruto]/myprivate/gatbx[Sheffield]/reins.m | 5,452 | utf_8 | 270d878d55dc8b5ca7eb8b327560b146 | % REINS.M (RE-INSertion of offspring in population replacing parents)
%
% This function reinserts offspring in the population.
%
% Syntax: [Chrom, ObjVCh] = reins(Chrom, SelCh, SUBPOP, InsOpt, ObjVCh, ObjVSel)
%
% Input parameters:
% Chrom - Matrix containing the individuals (parents) of the current
% ... |
github | xenron/sandbox-da-matlab-master | mut.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_6_Code/libsvm-mat-2[1].89-3[FarutoUltimate3.0Mcode]/implement[by faruto]/myprivate/gatbx[Sheffield]/mut.m | 1,556 | utf_8 | 97652aabfb892dcbbd240102963cfa0a | % MUT.m
%
% This function takes the representation of the current population,
% mutates each element with given probability and returns the resulting
% population.
%
% Syntax: NewChrom = mut(OldChrom,Pm,BaseV)
%
% Input parameters:
%
% OldChrom - A matrix containing the chromosomes of the
% current population. Ea... |
github | xenron/sandbox-da-matlab-master | recmut.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_6_Code/libsvm-mat-2[1].89-3[FarutoUltimate3.0Mcode]/implement[by faruto]/myprivate/gatbx[Sheffield]/recmut.m | 4,735 | utf_8 | e7037b945697583b7b681ae93ef56665 | % RECLIN.M (line RECombination with MUTation features)
%
% This function performs line recombination with mutation features between
% pairs of individuals and returns the new individuals after mating.
%
% Syntax: NewChrom = recmut(OldChrom, FieldDR, MutOpt)
%
% Input parameters:
% OldChrom - Matrix containin... |
github | xenron/sandbox-da-matlab-master | xovsprs.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_6_Code/libsvm-mat-2[1].89-3[FarutoUltimate3.0Mcode]/implement[by faruto]/myprivate/gatbx[Sheffield]/xovsprs.m | 1,059 | utf_8 | bd0059a9b0685fb0d25ad669c7de984e | % XOVSPRS.M (CROSSOVer Single-Point with Reduced Surrogate)
%
% This function performs single-point 'reduced surrogate' crossover between
% pairs of individuals and returns the current generation after mating.
%
% Syntax: NewChrom = xovsprs(OldChrom, XOVR)
%
% Input parameters:
% OldChrom - Matrix containing... |
github | xenron/sandbox-da-matlab-master | scaling.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_6_Code/libsvm-mat-2[1].89-3[FarutoUltimate3.0Mcode]/implement[by faruto]/myprivate/gatbx[Sheffield]/scaling.m | 1,219 | utf_8 | d8872170a387a6e841955b0efd3456e1 | % SCALING.m - linear fitness scaling
%
% This function implements a linear fitness scaling algorithm as described
% by Goldberg in "Genetic Algorithms in Search, Optimization and Machine
% Learning", Addison Wesley, 1989. It use is not recommended when fitness
% functions produce negative results as the scaling will b... |
github | xenron/sandbox-da-matlab-master | crtrp.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_6_Code/libsvm-mat-2[1].89-3[FarutoUltimate3.0Mcode]/implement[by faruto]/myprivate/gatbx[Sheffield]/crtrp.m | 2,039 | utf_8 | 1c83222a36bb7c88e41346cac82d549d | % CRTRP.M (CReaTe an initial (Real-value) Population)
%
% This function creates a population of given size of random real-values.
%
% Syntax: Chrom = crtrp(Nind,FieldDR);
%
% Input parameters:
% Nind - A scalar containing the number of individuals in the new
% population.
%
% Fi... |
github | xenron/sandbox-da-matlab-master | crtbp.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_6_Code/libsvm-mat-2[1].89-3[FarutoUltimate3.0Mcode]/implement[by faruto]/myprivate/gatbx[Sheffield]/crtbp.m | 2,116 | utf_8 | 0262d6199e6215c6de17ffcdd480c09e | % CRTP.m - Create an initial population
%
% This function creates a binary population of given size and structure.
%
% Syntax: [Chrom Lind BaseV] = crtbp(Nind, Lind, Base)
%
% Input Parameters:
%
% Nind - Either a scalar containing the number of individuals
% in the new population or a row vector of length two
% ... |
github | xenron/sandbox-da-matlab-master | rep.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_6_Code/libsvm-mat-2[1].89-3[FarutoUltimate3.0Mcode]/implement[by faruto]/myprivate/gatbx[Sheffield]/rep.m | 1,163 | utf_8 | 522fc66ca0b4d8c634ff478c54fc3174 | % REP.m Replicate a matrix
%
% This function replicates a matrix in both dimensions.
%
% Syntax: MatOut = rep(MatIn,REPN);
%
% Input parameters:
% MatIn - Input Matrix (before replicating)
%
% REPN - Vector of 2 numbers, how many replications in each dimension
% REPN(1): replicate... |
github | xenron/sandbox-da-matlab-master | rws.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_6_Code/libsvm-mat-2[1].89-3[FarutoUltimate3.0Mcode]/implement[by faruto]/myprivate/gatbx[Sheffield]/rws.m | 1,060 | utf_8 | 3e57371be37c2afe31e534bacac38ef1 | % RWS.m - Roulette Wheel Selection
%
% Syntax:
% NewChrIx = rws(FitnV, Nsel)
%
% This function selects a given number of individuals Nsel from a
% population. FitnV is a column vector containing the fitness
% values of the individuals in the population.
%
% The function retur... |
github | xenron/sandbox-da-matlab-master | recint.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_6_Code/libsvm-mat-2[1].89-3[FarutoUltimate3.0Mcode]/implement[by faruto]/myprivate/gatbx[Sheffield]/recint.m | 1,841 | utf_8 | 2e2ce4e7253b27b11965de41bbb06e97 | % RECINT.M (RECombination extended INTermediate)
%
% This function performs extended intermediate recombination between
% pairs of individuals and returns the new individuals after mating.
%
% Syntax: NewChrom = recint(OldChrom, XOVR)
%
% Input parameters:
% OldChrom - Matrix containing the chromosomes of th... |
github | xenron/sandbox-da-matlab-master | xovdp.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_6_Code/libsvm-mat-2[1].89-3[FarutoUltimate3.0Mcode]/implement[by faruto]/myprivate/gatbx[Sheffield]/xovdp.m | 1,011 | utf_8 | 307a96a23a58ae75230f93ac3305abdd | % XOVDP.M (CROSSOVer Double Point)
%
% This function performs double point crossover between pairs of
% individuals and returns the current generation after mating.
%
% Syntax: NewChrom = xovdp(OldChrom, XOVR)
%
% Input parameters:
% OldChrom - Matrix containing the chromosomes of the old
% p... |
github | xenron/sandbox-da-matlab-master | resplot.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_6_Code/libsvm-mat-2[1].89-3[FarutoUltimate3.0Mcode]/implement[by faruto]/myprivate/gatbx[Sheffield]/resplot.m | 2,025 | utf_8 | 0f9e36690c2696ad8733a25ca62f6e66 | % RESPLOT.M (RESult PLOTing)
%
% This function plots some results during computation.
%
% Syntax: resplot(Chrom,IndAll,ObjV,Best,gen)
%
% Input parameters:
% Chrom - Matrix containing the chromosomes of the current
% population. Each line corresponds to one individual.
% IndAll - Matr... |
github | xenron/sandbox-da-matlab-master | mutbga.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_6_Code/libsvm-mat-2[1].89-3[FarutoUltimate3.0Mcode]/implement[by faruto]/myprivate/gatbx[Sheffield]/mutbga.m | 4,831 | utf_8 | 798dcff17df5007819ffccc1692be180 | % MUTBGA.M (real-value MUTation like Breeder Genetic Algorithm)
%
% This function takes a matrix OldChrom containing the real
% representation of the individuals in the current population,
% mutates the individuals with probability MutR and returns
% the resulting population.
%
% This function implements the muta... |
github | xenron/sandbox-da-matlab-master | xovdprs.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_6_Code/libsvm-mat-2[1].89-3[FarutoUltimate3.0Mcode]/implement[by faruto]/myprivate/gatbx[Sheffield]/xovdprs.m | 1,059 | utf_8 | 1a80762a7f575ac6f9b3814857714a63 | % XOVDPRS.M (CROSSOVer Double-Point with Reduced Surrogate)
%
% This function performs double-point 'reduced surrogate' crossover between
% pairs of individuals and returns the current generation after mating.
%
% Syntax: NewChrom = xovdprs(OldChrom, XOVR)
%
% Input parameters:
% OldChrom - Matrix containing... |
github | xenron/sandbox-da-matlab-master | mutate.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_6_Code/libsvm-mat-2[1].89-3[FarutoUltimate3.0Mcode]/implement[by faruto]/myprivate/gatbx[Sheffield]/mutate.m | 3,356 | utf_8 | 76b01fbb1235eaa8ad0d2b8e6c202e52 | % MUTATE.M (MUTATion high-level function)
%
% This function takes a matrix OldChrom containing the
% representation of the individuals in the current population,
% mutates the individuals and returns the resulting population.
%
% The function handles multiple populations and calls the low-level
% mutation functi... |
github | xenron/sandbox-da-matlab-master | crtbase.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_6_Code/libsvm-mat-2[1].89-3[FarutoUltimate3.0Mcode]/implement[by faruto]/myprivate/gatbx[Sheffield]/crtbase.m | 1,122 | utf_8 | 4992ebac5f7aa555598ac6fb56477894 | % CRTBASE.m - Create base vector
%
% This function creates a vector containing the base of the loci
% in a chromosome.
%
% Syntax: BaseVec = crtbase(Lind, Base)
%
% Input Parameters:
%
% Lind - A scalar or vector containing the lengths
% of the alleles. Sum(Lind) is the length of
% the corresponding chromoso... |
github | xenron/sandbox-da-matlab-master | xovsh.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_6_Code/libsvm-mat-2[1].89-3[FarutoUltimate3.0Mcode]/implement[by faruto]/myprivate/gatbx[Sheffield]/xovsh.m | 1,001 | utf_8 | 8351ff203d7566d23a533028f1fc42d2 | % XOVSH.M (CROSSOVer SHuffle)
%
% This function performs shuffle crossover between pairs of
% individuals and returns the current generation after mating.
%
% Syntax: NewChrom = xovsh(OldChrom, XOVR)
%
% Input parameters:
% OldChrom - Matrix containing the chromosomes of the old
% population.... |
github | xenron/sandbox-da-matlab-master | reclin.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_6_Code/libsvm-mat-2[1].89-3[FarutoUltimate3.0Mcode]/implement[by faruto]/myprivate/gatbx[Sheffield]/reclin.m | 1,897 | utf_8 | 1b854d6c172c3c64433646f4815e800b | % RECLIN.M (RECombination extended LINe)
%
% This function performs extended line recombination between
% pairs of individuals and returns the new individuals after mating.
%
% Syntax: NewChrom = reclin(OldChrom, XOVR)
%
% Input parameters:
% OldChrom - Matrix containing the chromosomes of the old
% ... |
github | xenron/sandbox-da-matlab-master | xovmp.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_6_Code/libsvm-mat-2[1].89-3[FarutoUltimate3.0Mcode]/implement[by faruto]/myprivate/gatbx[Sheffield]/xovmp.m | 2,712 | utf_8 | 2fcf985e764ebd2f8abf1c4efc9d9b44 | % XOVMP.m Multi-point crossover
%
% Syntax: NewChrom = xovmp(OldChrom, Px, Npt, Rs)
%
% This function takes a matrix OldChrom containing the binary
% representation of the individuals in the current population,
% applies crossover to consecutive pairs of individuals with
% ... |
github | xenron/sandbox-da-matlab-master | xovsp.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_6_Code/libsvm-mat-2[1].89-3[FarutoUltimate3.0Mcode]/implement[by faruto]/myprivate/gatbx[Sheffield]/xovsp.m | 1,012 | utf_8 | 930745320d1d2c50db84573794038686 | % XOVSP.M (CROSSOVer Single-Point)
%
% This function performs single-point crossover between pairs of
% individuals and returns the current generation after mating.
%
% Syntax: NewChrom = xovsp(OldChrom, XOVR)
%
% Input parameters:
% OldChrom - Matrix containing the chromosomes of the old
% ... |
github | xenron/sandbox-da-matlab-master | pso.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_10_Code/PSO_ToolBox/psotb-beta-0.3/pso.m | 7,374 | utf_8 | 06efce0d4632cb2bb5cee37f242aa50b | %PSO >> function for the PSO ALGORITHM
%
% USAGES: 1.) [fxmin, xmin, Swarm, history] = PSO(psoOptions);
% 2.) [fxmin, xmin, Swarm, history] = PSO;
% 3.) fxmin = PSO(psoOptions);
% 3.) PSO
% etc.
%
% Arguments : psoOptions--> A Matlab stucture containing all PSO related opt... |
github | xenron/sandbox-da-matlab-master | get_psoOptions.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_10_Code/PSO_ToolBox/psotb-beta-0.3/get_psoOptions.m | 9,690 | utf_8 | 0005ee2bcecb230e44c97e136eb00247 | %get_psoOptions >> A function to get an "options structure" that is used to set various option of the PSO Algorithm.
%
% Usage : psoOptions = get_psoOptions
% Arguments : None
% Return Values : psoOptions--> A Matlab structure. It is further divided into the following structures.
% ... |
github | xenron/sandbox-da-matlab-master | DrawSwarm.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_10_Code/PSO_ToolBox/psotb-beta-0.3/DrawSwarm.m | 693 | utf_8 | e57d8d0d45526cb7af16e1f5682974f7 | %DrawSwarm >> Internal function of psotoolbox.
% Purpose: To draw a visual display of the Swarm.
%
% You shouldn't need to mess around with this fn. if u don't wanna change the visualization.
%
% see also: pso.m
%
function DrawSwarm(Swarm, SwarmSize, Generation, Dimensions, GBest, vizAxes)
X = Swarm';
if Dimensions >... |
github | xenron/sandbox-da-matlab-master | RunExp.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_10_Code/PSO_ToolBox/psotb-beta-0.3/RunExp.m | 7,304 | utf_8 | 5754065878942b9df67d17cf78773295 | %RunExp >> Automation function
% Usage : RunExp(noRuns, ExitAction) %e.g. RunExp(25, 1); -> Runs each experminet for 25 trials and Exits matlab when doen.
% Arguments : (optional) noRuns -> Integer -> Number of trials per experiment
% (optional) ExitAction -> Integer -> Action to perform on completi... |
github | xenron/sandbox-da-matlab-master | show_psoOptions.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_10_Code/PSO_ToolBox/psotb-beta-0.3/show_psoOptions.m | 1,667 | utf_8 | ee0f1f6588bb4448ffff53dfd1f5aa51 | %show_psoOptions >> A function to read and display the psoOptions structure.
%
% Usage : strOptions = show_psoOptions( psoOptions )
% Arguments : A structure containing various options for PSO
% Return Values : A string containing the information abt the elements of the provided structure.
%
% History ... |
github | xenron/sandbox-da-matlab-master | Rastrigrin.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_10_Code/PSO_ToolBox/psotb-beta-0.3/functions/Rastrigrin.m | 363 | utf_8 | 8722cd5f6c02a4a3792797a617d3c568 | %The Rastrigrin function for use with the psotoolbox
%
% Function Description:
% Equation -> sum (x(i)^2 - 10 * cos(2 * pi * x(i)) + 10)
% xmin = [0, 0, 0.....0] (all zeoes)
% fxmin = 0 (zero)
function Rastred = Rastrigrin(Swarm)
[SwarmSize, Dim] = size(Swarm);
Rastred = Dim * 10 + sum(((S... |
github | xenron/sandbox-da-matlab-master | DeJong.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_10_Code/PSO_ToolBox/psotb-beta-0.3/functions/DeJong.m | 289 | utf_8 | beea0113067ccc10bba3bc1bec521920 | %The DeJong (Sphere) function for use with the psotoolbox
%
% Function Description:
% Equation -> sum ( x(i)^2 )
% xmin = [0, 0, 0.....0] (all zeroes)
% fxmin = 0 (zero)
function Dejed = DeJong(Swarm)
[SwarmSize, Dim] = size(Swarm);
Dejed = sum((Swarm .^2)')'; |
github | xenron/sandbox-da-matlab-master | Griewank.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_10_Code/PSO_ToolBox/psotb-beta-0.3/functions/Griewank.m | 421 | utf_8 | 28a07a64ab5afb67e6c5aa035295dd67 | %The Griewank function for use with the psotoolbox
%
% Function Description:
% Equation -> sum(((x(i).^2) / 4000)')' - prod(cos(x(i) ./ sqrt(i))')' + 1
% xmin = [0, 0, 0.....0] (all zeroes)
% fxmin = 0 (zero)
function Gred = Griewank(Swarm);
[SwarmSize, Dim] = size(Swarm);
indices = repmat(... |
github | xenron/sandbox-da-matlab-master | Rosenbrock.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_10_Code/PSO_ToolBox/psotb-beta-0.3/functions/Rosenbrock.m | 515 | utf_8 | d854a99553349e30f0ca4b51054f5613 | %The Rosenbrock function for use with the psotoolbox
%
% Function Description:
% Equation -> sum ( 100 * (x(i+1) - x(i)^2)^2 + (1-x(i))^2 )
% xmin = [1, 1, 1.....1] (all ones)
% fxmin = 0 (zero)
function Rosened = Rosenbrock(Swarm)
[SwarmSize, Dim] = size(Swarm);
Swarm1 = Swarm(:, 1:(Dim-1)... |
github | xenron/sandbox-da-matlab-master | psoboundspenalize.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_10_Code/PSO_ToolBox/psopt/psoboundspenalize.m | 2,879 | utf_8 | c84fa7bc9d42c2fe4265d21923a91546 | function state = ...
psoboundspenalize(state,Aineq,bineq,Aeq,beq,LB,UB,nonlcon,options)
% Penalty-based constraint enforcement method.
% Unpack variables from state structure (necessary for parfor)
x = state.Population ;
v = state.Velocities ;
n = size(state.Population,1) ;
nvars = size(x,1) ;
OutOfBounds = false(... |
github | xenron/sandbox-da-matlab-master | psoiterate.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_10_Code/PSO_ToolBox/psopt/psoiterate.m | 2,182 | utf_8 | 98361e6f7daee3d6e4b9ad481e9665b6 | function [state,flag] = psoiterate(options,state,flag)
% Updates swarm positions and velocities. Called to iterate the swarm from
% the main PSO function. This function can handle binary and double-vector
% "genomes".
% Weightings for inertia, local, and global influence.
C0 = state.ParticleInertia ;
C1 = options.Cogn... |
github | xenron/sandbox-da-matlab-master | psocheckbounds.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_10_Code/PSO_ToolBox/psopt/private/psocheckbounds.m | 4,590 | utf_8 | bf09d934747ca71086922191dccb549c | function state = ...
psocheckbounds(options,state,Aineq,bineq,Aeq,beq,LB,UB,nonlcon)
% Check the the swarm population against all constraints.
%
% May 15, 2013
% Deprecated, replaced by PSOBOUNDSPENALIZE in the ./psopt folder.
x = state.Population ;
v = state.Velocities ;
n = size(state.Population,1) ;
state.OutOf... |
github | xenron/sandbox-da-matlab-master | pso_Trelea_vectorized.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_10_Code/PSO_ToolBox/PSOt/pso_Trelea_vectorized.m | 22,223 | utf_8 | d95ae17f4e03562985edb35a3ce51c99 | % pso_Trelea_vectorized.m
% a generic particle swarm optimizer
% to find the minimum or maximum of any
% MISO matlab function
%
% Implements Common, Trelea type 1 and 2, and Clerc's class 1". It will
% also automatically try to track to a changing environment (with varied
% success - BKB 3/18/05)
%
% This vectorized v... |
github | xenron/sandbox-da-matlab-master | DeJong_f2.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_10_Code/PSO_ToolBox/PSOt/testfunctions/DeJong_f2.m | 705 | utf_8 | f474c060e61ab63d089b22de5a3cdcd9 | % DeJong_f2.m
% De Jong's f2 function, also called a Rosenbrock Variant
% This is a 2D only equation
%
% described by Clerc in ...
% http://clerc.maurice.free.fr/pso/Semi-continuous_challenge/Semi-continuous_challenge.htm
%
% used to test optimization/global minimization problems
% in Clerc's "Semi-continuous challeng... |
github | xenron/sandbox-da-matlab-master | ackley.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_10_Code/PSO_ToolBox/PSOt/testfunctions/ackley.m | 839 | utf_8 | f53febad1b1241ed2b82eb51990c494a | % ackley.m
% Ackley's function, from http://www.cs.vu.nl/~gusz/ecbook/slides/16
% and further shown at:
% http://clerc.maurice.free.fr/pso/Semi-continuous_challenge/Semi-continuous_challenge.htm
%
% commonly used to test optimization/global minimization problems
%
% f(x)= [ 20 + e ...
% -20*exp(-0.2*sqrt((1/n)*... |
github | xenron/sandbox-da-matlab-master | f6_spiral_dyn.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_10_Code/PSO_ToolBox/PSOt/testfunctions/f6_spiral_dyn.m | 842 | utf_8 | a68995830769a8c36f01a49a1b854227 | % f6_spiral_dyn.m
% Schaffer's F6 function
% commonly used to test optimization/global minimization problems
%
% This version moves the minimum about a Fermat Spiral
% according to the equation: r = a*(theta^2)
% theta is a function of time and is checked internally (not an input)
% x_center = r*cos(theta)
% y_ce... |
github | xenron/sandbox-da-matlab-master | f6_linear_dyn.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_10_Code/PSO_ToolBox/PSOt/testfunctions/f6_linear_dyn.m | 593 | utf_8 | ff08de37e8934d90aaf0da2cd9be2020 | % f6_linear_dyn.m
% Schaffer's F6 function
% commonly used to test optimization/global minimization problems
%
% This version moves the minimum linearly along a 45 deg angle in x,y space
% Brian Birge
% Rev 1.0
% 9/12/04
function [out]=f6_linear_dyn(in)
% parse input
x = in(:,1);
y = in(:,2);
% find current m... |
github | xenron/sandbox-da-matlab-master | NDparabola.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_10_Code/PSO_ToolBox/PSOt/testfunctions/NDparabola.m | 641 | utf_8 | 85e34a0950db121bff8caeefcc737538 | % NDparabola.m
% ND Parabola function (also called a Sphere function and DeJong's f1),
% described by Clerc...
% http://clerc.maurice.free.fr/pso/Semi-continuous_challenge/Semi-continuous_challenge.htm
%
% used to test optimization/global minimization problems
% in Clerc's "Semi-continuous challenge"
%
% f(x) = sum( x... |
github | xenron/sandbox-da-matlab-master | alpine.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_10_Code/PSO_ToolBox/PSOt/testfunctions/alpine.m | 617 | utf_8 | 350e9ce69d84cc997f59ab6d77b6c4e5 | % alpine.m
% ND Alpine function, described by Clerc...
% http://clerc.maurice.free.fr/pso/Semi-continuous_challenge/Semi-continuous_challenge.htm
%
% used to test optimization/global minimization problems
% in Clerc's "Semi-continuous challenge"
%
% f(x) = sum( abs(x.*sin(x) + 0.1.*x) )
%
% x = N element row vector c... |
github | xenron/sandbox-da-matlab-master | Griewank.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_10_Code/PSO_ToolBox/PSOt/testfunctions/Griewank.m | 1,175 | utf_8 | 1922426be7c11651ad663dd929a16606 | % Griewank.m
% Griewank function
% described by Clerc in ...
% http://clerc.maurice.free.fr/pso/Semi-continuous_challenge/Semi-continuous_challenge.htm
%
% used to test optimization/global minimization problems
% in Clerc's "Semi-continuous challenge"
%
% f(x) = sum((x-100).^2,2)./4000 - ...
% prod(cos((x-100).... |
github | xenron/sandbox-da-matlab-master | f6mod.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_10_Code/PSO_ToolBox/PSOt/testfunctions/f6mod.m | 675 | utf_8 | 35ebfbe0fff22261e101217b1604fe22 | % f6mod.m
% Schaffer's F6 function
% commonly used to test optimization/global minimization problems
%
% This version is a modified form, just the sum of 5 f6 functions with
% different centers to look at local minimum issues
% normal f6=
% z = 0.5+ (sin^2(sqrt(x^2+y^2))-0.5)/((1+0.01*(x^2+y^2))^2)
function [out]=f6mo... |
github | xenron/sandbox-da-matlab-master | Rastrigin.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_10_Code/PSO_ToolBox/PSOt/testfunctions/Rastrigin.m | 500 | utf_8 | 49633129edf0685033f0b4fc126a822c | % Rastrigin.m
% Rastrigin function
%
% used to test optimization/global minimization problems
%
% f(x) = sum([x.^2-10*cos(2*pi*x) + 10], 2);
%
% x = N element row vector containing [x0, x1, ..., xN]
% each row is processed independently,
% you can feed in matrices of timeXN no prob
%
% example: cost = Rastrigin([1,2;... |
github | xenron/sandbox-da-matlab-master | f6.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_10_Code/PSO_ToolBox/PSOt/testfunctions/f6.m | 299 | utf_8 | 6e328b2ad0f76540e9c80d87b5ad06dc | % f6.m
% Schaffer's F6 function
% commonly used to test optimization/global minimization problems
%
% z = 0.5+ (sin^2(sqrt(x^2+y^2))-0.5)/((1+0.01*(x^2+y^2))^2)
function [out]=f6(in)
x=in(:,1);
y=in(:,2);
num=sin(sqrt(x.^2+y.^2)).^2 - 0.5;
den=(1.0+0.01*(x.^2+y.^2)).^2;
out=0.5 +num./den;
|
github | xenron/sandbox-da-matlab-master | f6_bubbles_dyn.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_10_Code/PSO_ToolBox/PSOt/testfunctions/f6_bubbles_dyn.m | 1,458 | utf_8 | 00614b7d2beaf3ea99b48c5ccdd00063 | % f6_bubbles_dyn.m
% 2 separate Schaffer's F6 functions, one with min at [-8,-8] and the
% other with min at [8,8]
% as time goes on, each bubbles magnitude cycles up and down,
% they are 180 deg out of phase with each other
%
% commonly used to test optimization/global minimization problems
function [out]=f6_bubbles... |
github | xenron/sandbox-da-matlab-master | Rosenbrock.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_10_Code/PSO_ToolBox/PSOt/testfunctions/Rosenbrock.m | 697 | utf_8 | 9b342f29fa2367ba43883cb0b50432cb | % Rosenbrock.m
% Rosenbrock function
%
% described by Clerc in ...
% http://clerc.maurice.free.fr/pso/Semi-continuous_challenge/Semi-continuous_challenge.htm
%
% used to test optimization/global minimization problems
% in Clerc's "Semi-continuous challenge"
%
% f(x) = sum([ 100*(x(i+1) - x(i)^2)^2 + (x(i) -1)^2])
%
%... |
github | xenron/sandbox-da-matlab-master | tripod.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_10_Code/PSO_ToolBox/PSOt/testfunctions/tripod.m | 860 | utf_8 | 9e3c6b8565897f712d6297c5e041ebef | % tripod.m
% 2D tripod function, described by Clerc...
% http://clerc.maurice.free.fr/pso/Semi-continuous_challenge/Semi-continuous_challenge.htm
%
% used to test optimization/global minimization problems
% in Clerc's "Semi-continuous challenge"
%
% f(x)= [ p(x2)*(1+p(x1)) ...
% + abs(x1 + 50*p(x2)*(1-2*p(x1)))... |
github | xenron/sandbox-da-matlab-master | Foxhole.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_10_Code/PSO_ToolBox/PSOt/testfunctions/Foxhole.m | 1,232 | utf_8 | 21a1c5dd5e44f43ef92759b2e174b59c | % Foxhole.m
% Foxhole function, 2D multi-minima function
%
% from: http://www.cs.rpi.edu/~hornda/pres/node10.html
%
% f(x) = 0.002 + sum([1/(j + sum( [x(i) - a(i,j)].^6 ) )])
%
% x = 2 element row vector containing [ x, y ]
% each row is processed independently,
% you can feed in matrices of timeX2 no prob
%
% exampl... |
github | xenron/sandbox-da-matlab-master | DeJong_f4.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_10_Code/PSO_ToolBox/PSOt/testfunctions/DeJong_f4.m | 971 | utf_8 | 9df4774e7545c69c3ded2336203917ac | % DeJong_f4.m
% De Jong's f4 function, ND, no noise
%
% described by Clerc in ...
% http://clerc.maurice.free.fr/pso/Semi-continuous_challenge/Semi-continuous_challenge.htm
%
% used to test optimization/global minimization problems
% in Clerc's "Semi-continuous challenge"
%
% f(x) = sum( [1:N].*(in.^4), 2)
%
% x = N e... |
github | xenron/sandbox-da-matlab-master | DeJong_f3.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_10_Code/PSO_ToolBox/PSOt/testfunctions/DeJong_f3.m | 488 | utf_8 | 60082b5c3e0231c66b32f383ab9aca68 | % DeJong_f3.m
% De Jong's f3 function, ND, also called STEP
% from: http://www.cs.rpi.edu/~hornda/pres/node4.html
%
% f(x) = sum( floor(x) )
%
% x = N element row vector containing [ x0, x1,..., xN ]
% each row is processed independently,
% you can feed in matrices of timeXN no prob
%
% example: cost = DeJong_f3([1... |
github | xenron/sandbox-da-matlab-master | trainpso.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_10_Code/PSO_ToolBox/PSOt/nnet/trainpso.m | 11,390 | utf_8 | b0b9ca9bc6cf295c09d3d671aa51985d | %TRAINPSO Particle Swarm Optimization backpropagation.
%
% Syntax
%
% [net,tr,Ac,El] = trainpso(net,Pd,Tl,Ai,Q,TS,VV,TV)
% info = trainpso(code)
%
% Description
%
% TRAINPSO is a network training function that updates weight and
% bias values according to particle swarm optimization.
%
% TRAINPSO(NET... |
github | xenron/sandbox-da-matlab-master | pso_neteval.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_10_Code/PSO_ToolBox/PSOt/nnet/pso_neteval.m | 805 | utf_8 | d62a385fce2ad63d1382005e6800a61c | % pso_neteval.m
% function to evaluate a neural nets performance as called from
% the PSO function: pso_Trelea_vectorized.m and trainpso.m
%
% usage: cost = pso_neteval(x)
% where x is an MxN array of weights & biases
% M is particle index
% N is weight & bias index
% Brian Birge
% Rev 2.0
% 3/8/06
fun... |
github | xenron/sandbox-da-matlab-master | spiral_dyn.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_10_Code/PSO_ToolBox/PSOt/hiddenutils/spiral_dyn.m | 805 | utf_8 | 9ed110a6f7dc7937e4f689a5a3b912ee | % spiral_dyn.m
% returns x,y position along an archimedean spiral of degree n
% based on cputime, first time it is called is start time
%
% based on: r = a*(theta^n)
%
% usage: [x_cnt,y_cnt] = spiral_dyn(n,a)
% i.e.,
% n = 2 (Fermat)
% = 1 (Archimedes)
% = -1 (Hyberbolic)
% = -2 (Lituus)
% Brian Birge... |
github | xenron/sandbox-da-matlab-master | linear_dyn.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_10_Code/PSO_ToolBox/PSOt/hiddenutils/linear_dyn.m | 724 | utf_8 | c630c42d5de136b31ca954328cde13d2 | % linear_dyn.m
% returns an offset that can be added to data that increases linearly with
% time, based on cputime, first time it is called is start time
%
% equation is: offset = (cputime - tnot)*scalefactor
% where tnot = cputime at the first call
% scalefactor = value that slows or speeds up linear movement
... |
github | xenron/sandbox-da-matlab-master | regRF_predict.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_8_Code/RandomForest/randomforest-matlab/RF_Reg_C/regRF_predict.m | 986 | utf_8 | 12601a7e5a27c8772b59437808384bbe | %**************************************************************
%* mex interface to Andy Liaw et al.'s C code (used in R package randomForest)
%* Added by Abhishek Jaiantilal ( abhishek.jaiantilal@colorado.edu )
%* License: GPLv2
%* Version: 0.02
%
% Calls Regression Random Forest
% A wrapper matlab file that calls the... |
github | xenron/sandbox-da-matlab-master | regRF_train.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_8_Code/RandomForest/randomforest-matlab/RF_Reg_C/regRF_train.m | 12,863 | utf_8 | a9c73de9b026cf655cbb18496e685f8c | %**************************************************************
%* mex interface to Andy Liaw et al.'s C code (used in R package randomForest)
%* Added by Abhishek Jaiantilal ( abhishek.jaiantilal@colorado.edu )
%* License: GPLv2
%* Version: 0.02
%
% Calls Regression Random Forest
% A wrapper matlab file that calls th... |
github | xenron/sandbox-da-matlab-master | compile_windows.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_8_Code/RandomForest/randomforest-matlab/RF_Reg_C/compile_windows.m | 801 | utf_8 | 1a638f868f9498ca3a5f980c4a5a03e7 | % ********************************************************************
% * mex File compiling code for Random Forest (for windows)
% * mex interface to Andy Liaw et al.'s C code (used in R package randomForest)
% * Added by Abhishek Jaiantilal ( abhishek.jaiantilal@colorado.edu )
% * License: GPLv2
% * Version: 0.02
% ... |
github | xenron/sandbox-da-matlab-master | compile_linux.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_8_Code/RandomForest/randomforest-matlab/RF_Reg_C/compile_linux.m | 952 | utf_8 | 69f27cce34b27de861e600f366e71001 | % ********************************************************************
% * mex File compiling code for Random Forest (for linux)
% * mex interface to Andy Liaw et al.'s C code (used in R package randomForest)
% * Added by Abhishek Jaiantilal ( abhishek.jaiantilal@colorado.edu )
% * License: GPLv2
% * Version: 0.02
% *... |
github | xenron/sandbox-da-matlab-master | classRF_predict.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_8_Code/RandomForest/randomforest-matlab/RF_Class_C/classRF_predict.m | 2,166 | utf_8 | 7e026fb9b31f99feae58d36b9cf6c2e0 | %**************************************************************
%* mex interface to Andy Liaw et al.'s C code (used in R package randomForest)
%* Added by Abhishek Jaiantilal ( abhishek.jaiantilal@colorado.edu )
%* License: GPLv2
%* Version: 0.02
%
% Calls Classification Random Forest
% A wrapper matlab file that calls... |
github | xenron/sandbox-da-matlab-master | compile_windows.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_8_Code/RandomForest/randomforest-matlab/RF_Class_C/compile_windows.m | 1,589 | utf_8 | dace2fcb13032c76c27364b1a5b24a33 | % ********************************************************************
% * mex File compiling code for Random Forest (for linux)
% * mex interface to Andy Liaw et al.'s C code (used in R package randomForest)
% * Added by Abhishek Jaiantilal ( abhishek.jaiantilal@colorado.edu )
% * License: GPLv2
% * Version: 0.02
% **... |
github | xenron/sandbox-da-matlab-master | classRF_train.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_8_Code/RandomForest/randomforest-matlab/RF_Class_C/classRF_train.m | 14,829 | utf_8 | 82a321d0a7c77f33b104acec4394c6ee | %**************************************************************
%* mex interface to Andy Liaw et al.'s C code (used in R package randomForest)
%* Added by Abhishek Jaiantilal ( abhishek.jaiantilal@colorado.edu )
%* License: GPLv2
%* Version: 0.02
%
% Calls Classification Random Forest
% A wrapper matlab file that calls... |
github | xenron/sandbox-da-matlab-master | compile_linux.m | .m | sandbox-da-matlab-master/src/dg/machine_learning_matlab/Class_8_Code/RandomForest/randomforest-matlab/RF_Class_C/compile_linux.m | 557 | utf_8 | c21b7b493153f2254a8a2c4d7be848f1 | % ********************************************************************
% * mex File compiling code for Random Forest (for linux)
% * mex interface to Andy Liaw et al.'s C code (used in R package randomForest)
% * Added by Abhishek Jaiantilal ( abhishek.jaiantilal@colorado.edu )
% * License: GPLv2
% * Version: 0.02
% **... |
github | fabriziogiuliano/wireless-mac-processor-master | vb_decoder_top_config.m | .m | wireless-mac-processor-master/wmp-engine/warp/Mango_802.11_RefDes_v1.2.0_wmp/pcores/wlan_phy_rx_pmd_axiw_v2_04_i/mdlsrc/blackboxes/vb_decoder_top_config.m | 4,577 | utf_8 | a5d03039069264527a6e82fb9ad6e823 |
function vb_decoder_top_config(this_block)
% Revision History:
%
% 13-Jul-2013 (13:25 hours):
% Original code was machine generated by Xilinx's System Generator after parsing
% S:\work\wlan\sysgen\wlan_phy_rx\decoder_dev\blackboxes\vb_decoder_top.v
%
%
this_block.setTopLevelLanguage('Veril... |
github | davheld/GOTURN-master | quantitativeEvaluationFScore_poly.m | .m | GOTURN-master/scripts/Fscore_v1.0/quantitativeEvaluationFScore_poly.m | 3,015 | utf_8 | 8b64681d94ccfa123be441066cdb89dd | %% The function takes three inputs.
%% trk_output_File is the path to the tracking output file in format of [frameNumber X1(topLeft) Y1(topLeft) Width Height]
%% ann_File in the format of ALOV++ released annotations
function fs = quantitativeEvaluationFScore_poly(trk_output_File, ann_File, thetas)
%% Read OutPut
%f... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.