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找到约 4,670 项符合「Probability」的源代码

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h xcsmacros.h

/* / (XCS-C 1.2) / ------------------------------------ / Learning Classifier System based on accuracy / / by / Martin V. Butz / Illinois Genetic Algorithms Laboratory (IlliGAL) /
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m genhan_two_stage.m

%TITLE: GEHAN'S TWO STAGE DESIGN% %SOURCE OF FORMULA: P14, CHAPTER 4, STA 526:CLINICAL DESIGN% %DESCRIPTION OF Gehan's Two Stage Design:% %Gehan's two stage design is used to evaluate the a
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htm chap06.htm

Intro to Algorithms: CHAPTER 6: COUNTING AND PROBABILITY
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m pbnaij.m

function pij = pbnAij(F,varF,nf,nv,cij,i,j,p) % pij = pbnAij(F,varF,nf,nv,cij,i,j,p) - transition prob. between two states % This function returns the ij-th entry (probability) in the state % tra
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m mutate.m

function out=mutate(in,pmutate); % % Mutate the incoming chromasome % with a probability of mutating % each string of pmutate. % % This file takes only one member % of the overall population.
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1 consult.1

.EN .TH C4.5 1 .SH NAME .PP consult \- classify items using a decision tree .SH SYNOPSIS .PP .B consult [ \fB-f\fR FNS ] [ \fB-t\fR ] .SH DESCRIPTION .PP .I Consult reads a decision tree produced by c
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1 consultr.1

.EN .TH C4.5 1 .SH NAME .PP consultr \- classify items using a rule set .SH SYNOPSIS .PP .B consultr [ \fB-f\fR FNS ] [ \fB-t\fR ] .SH DESCRIPTION .PP .I Consultr reads a rule set produced by c4.5rule
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readme

Python-to-libsvm interface Introduction ============ Python (http://www.python.org/) is a programming language suitable for rapid development. This python-to-libsvm interface is developed so users
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readme

Python-to-libsvm interface Introduction ============ Python (http://www.python.org/) is a programming language suitable for rapid development. This python-to-libsvm interface is developed so users
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in g.in

150000 : Maximum number of iterations 1,0 : Switch to retain best model 1=yes, 0=no; type of bitstring rep 0 : Switch to write out details of each iteration 1
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