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131A_1_train_filter

131A_1_train_filter - EE131A Probabilities File...

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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % EE131A: Probabilities % % File: train_filter.m % % Author: Nikolaos Kontorinis % % Date: 12/01/04 % % Description: Computes the spam probabilities of the words contained % in the training files bad_freq.txt and good_freq.txt % ATTENTION: % The two files bad_freq.txt and good_freq.txt should be % in the same directory with the .m files. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% clear all; %Open the two files with the training sets fid_bad = fopen('bad_freq.txt','r'); fid_good = fopen('good_freq.txt','r'); Number_bad_words=370; Number_good_words=276; %Read the bad words and their frequencies for m = 1:Number_bad_words n=1; temp = fscanf(fid_bad,'%1c',1); while(~isletter(temp)&&~isfinite(str2double(temp))) %Won't work temp = fscanf(fid_bad,'%1c',1); %Without this end %--Ian Salman % temp = fscanf(fid_bad,'%1c',1); %Read one char each time. bad(m,n)=temp; while(~isspace(temp)) bad(m,n)=temp; temp = fscanf(fid_bad,'%1c',1); n=n+1; end f_bad(m) = fscanf(fid_bad,'%d \n',1); %Read the frequency. end words = bad; %words will hold all the words appearing in the training
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