algorithms.txt

最新的模式识别分类工具箱,希望对朋友们有用!

Ada_Boost;Num iter, type, params:;[100,'Stumps',100];L
EM;nGaussians [clss0,clss1]:;[1,1];S
K_L_nn_Rule;[Nr Neighbors, l (nr samples in agreement)]:;[5,3];L
Local_Polynomial;Num of test points:;10;S
LocBoost;[nBoosting, nEM, nOpt, Optimize]:;[10 10 30 1];L
LS; ; ;N
LVQ1;Number of partitions:;4;S
LVQ3;Number of partitions:;4;S
ML; ; ;N
ML_diag; ; ;N
Nearest_Neighbor;Num of nearest neighbors:;3;S
Parzen;Norm. factor for h, Kernel;[1,'Epanechnikov'];L
Perceptron;Num of iterations:;500;S
PNN;Gaussian width;1;S
Pocket;Num of iterations:;500;S
RCE;Maximum radius:;1;S
RDA;Lambda:;0.4;S
Store_Grabbag;Num of nearest neighbors:;3;S
Stumps; ; ;N
SVM;;[1 1000 1 1 0 0.5 2 2 50 1 1 0 10 40 0.001 100 1];L
Voted_Perceptron;#Prcptrn, Mthd, Mthd_P:;[7,'Linear',0.5];L
weightedKNNRule;k,file with weights :;[7,'weights'];L
None; ; ;N