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Bonjour, j'ai posé une question précédente qui a donné une réponse raisonnable et j'ai pensé que j'étais de return sur la bonne voie, Fuzzy c-means tcp dump clustering dans matlab. Le problème est l'étape de prétraitement des données ci-dessous tcp / udp que je voudrais exécuter à travers matlabs Algorithme de clustering fcm. Ma question:
1) Comment puis-je ou quelle serait la meilleure méthode pour convertir datatables de text dans les cellules en une valeur numérique? quelle devrait être la valeur numérique?
Edit: Mes données dans Excel ressemblent maintenant à ceci:
0,tcp,http,SF,239,486,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,8,8,0.00,0.00,0.00,0.00,1.00,0.00,0.00,19,19,1.00,0.00,0.05,0.00,0.00,0.00,0.00,0.00,normal. Voici un exemple de la façon dont je lirais datatables dans MATLAB. Vous avez besoin de deux choses: datatables elles-mêmes qui sont en format séparé par des virgules, ainsi que la list des fonctionnalités avec leurs types (numériques, nominaux).
%# read the list of features fid = fopen('kddcup.names','rt'); C = textscan(fid, '%s %s', 'Delimiter',':', 'HeaderLines',1); fclose(fid); %# determine type of features C{2} = regexprep(C{2}, '.$',''); %# remove "." at the end atsortingbNom = [ismember(C{2},'symbolic');true]; %# nominal features %# build format ssortingng used to read/parse the actual data frmt = cell(1,numel(C{1})); frmt( ismember(C{2},'continuous') ) = {'%f'}; %# numeric features: read as number frmt( ismember(C{2},'symbolic') ) = {'%s'}; %# nominal features: read as ssortingng frmt = [frmt{:}]; frmt = [frmt '%s']; %# add the class atsortingbute %# read dataset fid = fopen('kddcup.data','rt'); C = textscan(fid, frmt, 'Delimiter',','); fclose(fid); %# convert nominal atsortingbutes to numeric ind = find(atsortingbNom); G = cell(numel(ind),1); for i=1:numel(ind) [C{ind(i)},G{i}] = grp2idx( C{ind(i)} ); end %# all numeric dataset M = cell2mat(C);% # lire la list des fonctionnalités%# read the list of features fid = fopen('kddcup.names','rt'); C = textscan(fid, '%s %s', 'Delimiter',':', 'HeaderLines',1); fclose(fid); %# determine type of features C{2} = regexprep(C{2}, '.$',''); %# remove "." at the end atsortingbNom = [ismember(C{2},'symbolic');true]; %# nominal features %# build format ssortingng used to read/parse the actual data frmt = cell(1,numel(C{1})); frmt( ismember(C{2},'continuous') ) = {'%f'}; %# numeric features: read as number frmt( ismember(C{2},'symbolic') ) = {'%s'}; %# nominal features: read as ssortingng frmt = [frmt{:}]; frmt = [frmt '%s']; %# add the class atsortingbute %# read dataset fid = fopen('kddcup.data','rt'); C = textscan(fid, frmt, 'Delimiter',','); fclose(fid); %# convert nominal atsortingbutes to numeric ind = find(atsortingbNom); G = cell(numel(ind),1); for i=1:numel(ind) [C{ind(i)},G{i}] = grp2idx( C{ind(i)} ); end %# all numeric dataset M = cell2mat(C);fid = fopen ('kddcup.names', 'rt');%# read the list of features fid = fopen('kddcup.names','rt'); C = textscan(fid, '%s %s', 'Delimiter',':', 'HeaderLines',1); fclose(fid); %# determine type of features C{2} = regexprep(C{2}, '.$',''); %# remove "." at the end atsortingbNom = [ismember(C{2},'symbolic');true]; %# nominal features %# build format ssortingng used to read/parse the actual data frmt = cell(1,numel(C{1})); frmt( ismember(C{2},'continuous') ) = {'%f'}; %# numeric features: read as number frmt( ismember(C{2},'symbolic') ) = {'%s'}; %# nominal features: read as ssortingng frmt = [frmt{:}]; frmt = [frmt '%s']; %# add the class atsortingbute %# read dataset fid = fopen('kddcup.data','rt'); C = textscan(fid, frmt, 'Delimiter',','); fclose(fid); %# convert nominal atsortingbutes to numeric ind = find(atsortingbNom); G = cell(numel(ind),1); for i=1:numel(ind) [C{ind(i)},G{i}] = grp2idx( C{ind(i)} ); end %# all numeric dataset M = cell2mat(C);C = textscan (fid, '% s% s', 'Delimiter', ':', 'HeaderLines', 1);%# read the list of features fid = fopen('kddcup.names','rt'); C = textscan(fid, '%s %s', 'Delimiter',':', 'HeaderLines',1); fclose(fid); %# determine type of features C{2} = regexprep(C{2}, '.$',''); %# remove "." at the end atsortingbNom = [ismember(C{2},'symbolic');true]; %# nominal features %# build format ssortingng used to read/parse the actual data frmt = cell(1,numel(C{1})); frmt( ismember(C{2},'continuous') ) = {'%f'}; %# numeric features: read as number frmt( ismember(C{2},'symbolic') ) = {'%s'}; %# nominal features: read as ssortingng frmt = [frmt{:}]; frmt = [frmt '%s']; %# add the class atsortingbute %# read dataset fid = fopen('kddcup.data','rt'); C = textscan(fid, frmt, 'Delimiter',','); fclose(fid); %# convert nominal atsortingbutes to numeric ind = find(atsortingbNom); G = cell(numel(ind),1); for i=1:numel(ind) [C{ind(i)},G{i}] = grp2idx( C{ind(i)} ); end %# all numeric dataset M = cell2mat(C);fclose (fid);%# read the list of features fid = fopen('kddcup.names','rt'); C = textscan(fid, '%s %s', 'Delimiter',':', 'HeaderLines',1); fclose(fid); %# determine type of features C{2} = regexprep(C{2}, '.$',''); %# remove "." at the end atsortingbNom = [ismember(C{2},'symbolic');true]; %# nominal features %# build format ssortingng used to read/parse the actual data frmt = cell(1,numel(C{1})); frmt( ismember(C{2},'continuous') ) = {'%f'}; %# numeric features: read as number frmt( ismember(C{2},'symbolic') ) = {'%s'}; %# nominal features: read as ssortingng frmt = [frmt{:}]; frmt = [frmt '%s']; %# add the class atsortingbute %# read dataset fid = fopen('kddcup.data','rt'); C = textscan(fid, frmt, 'Delimiter',','); fclose(fid); %# convert nominal atsortingbutes to numeric ind = find(atsortingbNom); G = cell(numel(ind),1); for i=1:numel(ind) [C{ind(i)},G{i}] = grp2idx( C{ind(i)} ); end %# all numeric dataset M = cell2mat(C);% # déterminer le type de fonctionnalités%# read the list of features fid = fopen('kddcup.names','rt'); C = textscan(fid, '%s %s', 'Delimiter',':', 'HeaderLines',1); fclose(fid); %# determine type of features C{2} = regexprep(C{2}, '.$',''); %# remove "." at the end atsortingbNom = [ismember(C{2},'symbolic');true]; %# nominal features %# build format ssortingng used to read/parse the actual data frmt = cell(1,numel(C{1})); frmt( ismember(C{2},'continuous') ) = {'%f'}; %# numeric features: read as number frmt( ismember(C{2},'symbolic') ) = {'%s'}; %# nominal features: read as ssortingng frmt = [frmt{:}]; frmt = [frmt '%s']; %# add the class atsortingbute %# read dataset fid = fopen('kddcup.data','rt'); C = textscan(fid, frmt, 'Delimiter',','); fclose(fid); %# convert nominal atsortingbutes to numeric ind = find(atsortingbNom); G = cell(numel(ind),1); for i=1:numel(ind) [C{ind(i)},G{i}] = grp2idx( C{ind(i)} ); end %# all numeric dataset M = cell2mat(C);C {2} = regexprep (C {2}, '. $', '');%# read the list of features fid = fopen('kddcup.names','rt'); C = textscan(fid, '%s %s', 'Delimiter',':', 'HeaderLines',1); fclose(fid); %# determine type of features C{2} = regexprep(C{2}, '.$',''); %# remove "." at the end atsortingbNom = [ismember(C{2},'symbolic');true]; %# nominal features %# build format ssortingng used to read/parse the actual data frmt = cell(1,numel(C{1})); frmt( ismember(C{2},'continuous') ) = {'%f'}; %# numeric features: read as number frmt( ismember(C{2},'symbolic') ) = {'%s'}; %# nominal features: read as ssortingng frmt = [frmt{:}]; frmt = [frmt '%s']; %# add the class atsortingbute %# read dataset fid = fopen('kddcup.data','rt'); C = textscan(fid, frmt, 'Delimiter',','); fclose(fid); %# convert nominal atsortingbutes to numeric ind = find(atsortingbNom); G = cell(numel(ind),1); for i=1:numel(ind) [C{ind(i)},G{i}] = grp2idx( C{ind(i)} ); end %# all numeric dataset M = cell2mat(C);atsortingbNom = [ismember (C {2}, 'symbolique'); vrai];%# read the list of features fid = fopen('kddcup.names','rt'); C = textscan(fid, '%s %s', 'Delimiter',':', 'HeaderLines',1); fclose(fid); %# determine type of features C{2} = regexprep(C{2}, '.$',''); %# remove "." at the end atsortingbNom = [ismember(C{2},'symbolic');true]; %# nominal features %# build format ssortingng used to read/parse the actual data frmt = cell(1,numel(C{1})); frmt( ismember(C{2},'continuous') ) = {'%f'}; %# numeric features: read as number frmt( ismember(C{2},'symbolic') ) = {'%s'}; %# nominal features: read as ssortingng frmt = [frmt{:}]; frmt = [frmt '%s']; %# add the class atsortingbute %# read dataset fid = fopen('kddcup.data','rt'); C = textscan(fid, frmt, 'Delimiter',','); fclose(fid); %# convert nominal atsortingbutes to numeric ind = find(atsortingbNom); G = cell(numel(ind),1); for i=1:numel(ind) [C{ind(i)},G{i}] = grp2idx( C{ind(i)} ); end %# all numeric dataset M = cell2mat(C);% # caractéristiques nominales%# read the list of features fid = fopen('kddcup.names','rt'); C = textscan(fid, '%s %s', 'Delimiter',':', 'HeaderLines',1); fclose(fid); %# determine type of features C{2} = regexprep(C{2}, '.$',''); %# remove "." at the end atsortingbNom = [ismember(C{2},'symbolic');true]; %# nominal features %# build format ssortingng used to read/parse the actual data frmt = cell(1,numel(C{1})); frmt( ismember(C{2},'continuous') ) = {'%f'}; %# numeric features: read as number frmt( ismember(C{2},'symbolic') ) = {'%s'}; %# nominal features: read as ssortingng frmt = [frmt{:}]; frmt = [frmt '%s']; %# add the class atsortingbute %# read dataset fid = fopen('kddcup.data','rt'); C = textscan(fid, frmt, 'Delimiter',','); fclose(fid); %# convert nominal atsortingbutes to numeric ind = find(atsortingbNom); G = cell(numel(ind),1); for i=1:numel(ind) [C{ind(i)},G{i}] = grp2idx( C{ind(i)} ); end %# all numeric dataset M = cell2mat(C);% # string de format de construction utilisée pour lire / parsingr datatables réelles%# read the list of features fid = fopen('kddcup.names','rt'); C = textscan(fid, '%s %s', 'Delimiter',':', 'HeaderLines',1); fclose(fid); %# determine type of features C{2} = regexprep(C{2}, '.$',''); %# remove "." at the end atsortingbNom = [ismember(C{2},'symbolic');true]; %# nominal features %# build format ssortingng used to read/parse the actual data frmt = cell(1,numel(C{1})); frmt( ismember(C{2},'continuous') ) = {'%f'}; %# numeric features: read as number frmt( ismember(C{2},'symbolic') ) = {'%s'}; %# nominal features: read as ssortingng frmt = [frmt{:}]; frmt = [frmt '%s']; %# add the class atsortingbute %# read dataset fid = fopen('kddcup.data','rt'); C = textscan(fid, frmt, 'Delimiter',','); fclose(fid); %# convert nominal atsortingbutes to numeric ind = find(atsortingbNom); G = cell(numel(ind),1); for i=1:numel(ind) [C{ind(i)},G{i}] = grp2idx( C{ind(i)} ); end %# all numeric dataset M = cell2mat(C);frmt = cellule (1, numel (C {1}));%# read the list of features fid = fopen('kddcup.names','rt'); C = textscan(fid, '%s %s', 'Delimiter',':', 'HeaderLines',1); fclose(fid); %# determine type of features C{2} = regexprep(C{2}, '.$',''); %# remove "." at the end atsortingbNom = [ismember(C{2},'symbolic');true]; %# nominal features %# build format ssortingng used to read/parse the actual data frmt = cell(1,numel(C{1})); frmt( ismember(C{2},'continuous') ) = {'%f'}; %# numeric features: read as number frmt( ismember(C{2},'symbolic') ) = {'%s'}; %# nominal features: read as ssortingng frmt = [frmt{:}]; frmt = [frmt '%s']; %# add the class atsortingbute %# read dataset fid = fopen('kddcup.data','rt'); C = textscan(fid, frmt, 'Delimiter',','); fclose(fid); %# convert nominal atsortingbutes to numeric ind = find(atsortingbNom); G = cell(numel(ind),1); for i=1:numel(ind) [C{ind(i)},G{i}] = grp2idx( C{ind(i)} ); end %# all numeric dataset M = cell2mat(C);frmt (ismember (C {2}, 'continue')) = {'% f'};%# read the list of features fid = fopen('kddcup.names','rt'); C = textscan(fid, '%s %s', 'Delimiter',':', 'HeaderLines',1); fclose(fid); %# determine type of features C{2} = regexprep(C{2}, '.$',''); %# remove "." at the end atsortingbNom = [ismember(C{2},'symbolic');true]; %# nominal features %# build format ssortingng used to read/parse the actual data frmt = cell(1,numel(C{1})); frmt( ismember(C{2},'continuous') ) = {'%f'}; %# numeric features: read as number frmt( ismember(C{2},'symbolic') ) = {'%s'}; %# nominal features: read as ssortingng frmt = [frmt{:}]; frmt = [frmt '%s']; %# add the class atsortingbute %# read dataset fid = fopen('kddcup.data','rt'); C = textscan(fid, frmt, 'Delimiter',','); fclose(fid); %# convert nominal atsortingbutes to numeric ind = find(atsortingbNom); G = cell(numel(ind),1); for i=1:numel(ind) [C{ind(i)},G{i}] = grp2idx( C{ind(i)} ); end %# all numeric dataset M = cell2mat(C);% # fonctions numériques: lire comme numéro%# read the list of features fid = fopen('kddcup.names','rt'); C = textscan(fid, '%s %s', 'Delimiter',':', 'HeaderLines',1); fclose(fid); %# determine type of features C{2} = regexprep(C{2}, '.$',''); %# remove "." at the end atsortingbNom = [ismember(C{2},'symbolic');true]; %# nominal features %# build format ssortingng used to read/parse the actual data frmt = cell(1,numel(C{1})); frmt( ismember(C{2},'continuous') ) = {'%f'}; %# numeric features: read as number frmt( ismember(C{2},'symbolic') ) = {'%s'}; %# nominal features: read as ssortingng frmt = [frmt{:}]; frmt = [frmt '%s']; %# add the class atsortingbute %# read dataset fid = fopen('kddcup.data','rt'); C = textscan(fid, frmt, 'Delimiter',','); fclose(fid); %# convert nominal atsortingbutes to numeric ind = find(atsortingbNom); G = cell(numel(ind),1); for i=1:numel(ind) [C{ind(i)},G{i}] = grp2idx( C{ind(i)} ); end %# all numeric dataset M = cell2mat(C);frmt (ismember (C {2}, 'symbolique')) = {'% s'};%# read the list of features fid = fopen('kddcup.names','rt'); C = textscan(fid, '%s %s', 'Delimiter',':', 'HeaderLines',1); fclose(fid); %# determine type of features C{2} = regexprep(C{2}, '.$',''); %# remove "." at the end atsortingbNom = [ismember(C{2},'symbolic');true]; %# nominal features %# build format ssortingng used to read/parse the actual data frmt = cell(1,numel(C{1})); frmt( ismember(C{2},'continuous') ) = {'%f'}; %# numeric features: read as number frmt( ismember(C{2},'symbolic') ) = {'%s'}; %# nominal features: read as ssortingng frmt = [frmt{:}]; frmt = [frmt '%s']; %# add the class atsortingbute %# read dataset fid = fopen('kddcup.data','rt'); C = textscan(fid, frmt, 'Delimiter',','); fclose(fid); %# convert nominal atsortingbutes to numeric ind = find(atsortingbNom); G = cell(numel(ind),1); for i=1:numel(ind) [C{ind(i)},G{i}] = grp2idx( C{ind(i)} ); end %# all numeric dataset M = cell2mat(C);% # caractéristiques nominales: lire comme string%# read the list of features fid = fopen('kddcup.names','rt'); C = textscan(fid, '%s %s', 'Delimiter',':', 'HeaderLines',1); fclose(fid); %# determine type of features C{2} = regexprep(C{2}, '.$',''); %# remove "." at the end atsortingbNom = [ismember(C{2},'symbolic');true]; %# nominal features %# build format ssortingng used to read/parse the actual data frmt = cell(1,numel(C{1})); frmt( ismember(C{2},'continuous') ) = {'%f'}; %# numeric features: read as number frmt( ismember(C{2},'symbolic') ) = {'%s'}; %# nominal features: read as ssortingng frmt = [frmt{:}]; frmt = [frmt '%s']; %# add the class atsortingbute %# read dataset fid = fopen('kddcup.data','rt'); C = textscan(fid, frmt, 'Delimiter',','); fclose(fid); %# convert nominal atsortingbutes to numeric ind = find(atsortingbNom); G = cell(numel(ind),1); for i=1:numel(ind) [C{ind(i)},G{i}] = grp2idx( C{ind(i)} ); end %# all numeric dataset M = cell2mat(C);frmt = [frmt {:}];%# read the list of features fid = fopen('kddcup.names','rt'); C = textscan(fid, '%s %s', 'Delimiter',':', 'HeaderLines',1); fclose(fid); %# determine type of features C{2} = regexprep(C{2}, '.$',''); %# remove "." at the end atsortingbNom = [ismember(C{2},'symbolic');true]; %# nominal features %# build format ssortingng used to read/parse the actual data frmt = cell(1,numel(C{1})); frmt( ismember(C{2},'continuous') ) = {'%f'}; %# numeric features: read as number frmt( ismember(C{2},'symbolic') ) = {'%s'}; %# nominal features: read as ssortingng frmt = [frmt{:}]; frmt = [frmt '%s']; %# add the class atsortingbute %# read dataset fid = fopen('kddcup.data','rt'); C = textscan(fid, frmt, 'Delimiter',','); fclose(fid); %# convert nominal atsortingbutes to numeric ind = find(atsortingbNom); G = cell(numel(ind),1); for i=1:numel(ind) [C{ind(i)},G{i}] = grp2idx( C{ind(i)} ); end %# all numeric dataset M = cell2mat(C);frmt = [frmt '% s'];%# read the list of features fid = fopen('kddcup.names','rt'); C = textscan(fid, '%s %s', 'Delimiter',':', 'HeaderLines',1); fclose(fid); %# determine type of features C{2} = regexprep(C{2}, '.$',''); %# remove "." at the end atsortingbNom = [ismember(C{2},'symbolic');true]; %# nominal features %# build format ssortingng used to read/parse the actual data frmt = cell(1,numel(C{1})); frmt( ismember(C{2},'continuous') ) = {'%f'}; %# numeric features: read as number frmt( ismember(C{2},'symbolic') ) = {'%s'}; %# nominal features: read as ssortingng frmt = [frmt{:}]; frmt = [frmt '%s']; %# add the class atsortingbute %# read dataset fid = fopen('kddcup.data','rt'); C = textscan(fid, frmt, 'Delimiter',','); fclose(fid); %# convert nominal atsortingbutes to numeric ind = find(atsortingbNom); G = cell(numel(ind),1); for i=1:numel(ind) [C{ind(i)},G{i}] = grp2idx( C{ind(i)} ); end %# all numeric dataset M = cell2mat(C);% # append l'atsortingbut de class%# read the list of features fid = fopen('kddcup.names','rt'); C = textscan(fid, '%s %s', 'Delimiter',':', 'HeaderLines',1); fclose(fid); %# determine type of features C{2} = regexprep(C{2}, '.$',''); %# remove "." at the end atsortingbNom = [ismember(C{2},'symbolic');true]; %# nominal features %# build format ssortingng used to read/parse the actual data frmt = cell(1,numel(C{1})); frmt( ismember(C{2},'continuous') ) = {'%f'}; %# numeric features: read as number frmt( ismember(C{2},'symbolic') ) = {'%s'}; %# nominal features: read as ssortingng frmt = [frmt{:}]; frmt = [frmt '%s']; %# add the class atsortingbute %# read dataset fid = fopen('kddcup.data','rt'); C = textscan(fid, frmt, 'Delimiter',','); fclose(fid); %# convert nominal atsortingbutes to numeric ind = find(atsortingbNom); G = cell(numel(ind),1); for i=1:numel(ind) [C{ind(i)},G{i}] = grp2idx( C{ind(i)} ); end %# all numeric dataset M = cell2mat(C);% # read dataset%# read the list of features fid = fopen('kddcup.names','rt'); C = textscan(fid, '%s %s', 'Delimiter',':', 'HeaderLines',1); fclose(fid); %# determine type of features C{2} = regexprep(C{2}, '.$',''); %# remove "." at the end atsortingbNom = [ismember(C{2},'symbolic');true]; %# nominal features %# build format ssortingng used to read/parse the actual data frmt = cell(1,numel(C{1})); frmt( ismember(C{2},'continuous') ) = {'%f'}; %# numeric features: read as number frmt( ismember(C{2},'symbolic') ) = {'%s'}; %# nominal features: read as ssortingng frmt = [frmt{:}]; frmt = [frmt '%s']; %# add the class atsortingbute %# read dataset fid = fopen('kddcup.data','rt'); C = textscan(fid, frmt, 'Delimiter',','); fclose(fid); %# convert nominal atsortingbutes to numeric ind = find(atsortingbNom); G = cell(numel(ind),1); for i=1:numel(ind) [C{ind(i)},G{i}] = grp2idx( C{ind(i)} ); end %# all numeric dataset M = cell2mat(C);fid = fopen ('kddcup.data', 'rt');%# read the list of features fid = fopen('kddcup.names','rt'); C = textscan(fid, '%s %s', 'Delimiter',':', 'HeaderLines',1); fclose(fid); %# determine type of features C{2} = regexprep(C{2}, '.$',''); %# remove "." at the end atsortingbNom = [ismember(C{2},'symbolic');true]; %# nominal features %# build format ssortingng used to read/parse the actual data frmt = cell(1,numel(C{1})); frmt( ismember(C{2},'continuous') ) = {'%f'}; %# numeric features: read as number frmt( ismember(C{2},'symbolic') ) = {'%s'}; %# nominal features: read as ssortingng frmt = [frmt{:}]; frmt = [frmt '%s']; %# add the class atsortingbute %# read dataset fid = fopen('kddcup.data','rt'); C = textscan(fid, frmt, 'Delimiter',','); fclose(fid); %# convert nominal atsortingbutes to numeric ind = find(atsortingbNom); G = cell(numel(ind),1); for i=1:numel(ind) [C{ind(i)},G{i}] = grp2idx( C{ind(i)} ); end %# all numeric dataset M = cell2mat(C);C = textscan (fid, frmt, 'Delimiter', ',');%# read the list of features fid = fopen('kddcup.names','rt'); C = textscan(fid, '%s %s', 'Delimiter',':', 'HeaderLines',1); fclose(fid); %# determine type of features C{2} = regexprep(C{2}, '.$',''); %# remove "." at the end atsortingbNom = [ismember(C{2},'symbolic');true]; %# nominal features %# build format ssortingng used to read/parse the actual data frmt = cell(1,numel(C{1})); frmt( ismember(C{2},'continuous') ) = {'%f'}; %# numeric features: read as number frmt( ismember(C{2},'symbolic') ) = {'%s'}; %# nominal features: read as ssortingng frmt = [frmt{:}]; frmt = [frmt '%s']; %# add the class atsortingbute %# read dataset fid = fopen('kddcup.data','rt'); C = textscan(fid, frmt, 'Delimiter',','); fclose(fid); %# convert nominal atsortingbutes to numeric ind = find(atsortingbNom); G = cell(numel(ind),1); for i=1:numel(ind) [C{ind(i)},G{i}] = grp2idx( C{ind(i)} ); end %# all numeric dataset M = cell2mat(C);fclose (fid);%# read the list of features fid = fopen('kddcup.names','rt'); C = textscan(fid, '%s %s', 'Delimiter',':', 'HeaderLines',1); fclose(fid); %# determine type of features C{2} = regexprep(C{2}, '.$',''); %# remove "." at the end atsortingbNom = [ismember(C{2},'symbolic');true]; %# nominal features %# build format ssortingng used to read/parse the actual data frmt = cell(1,numel(C{1})); frmt( ismember(C{2},'continuous') ) = {'%f'}; %# numeric features: read as number frmt( ismember(C{2},'symbolic') ) = {'%s'}; %# nominal features: read as ssortingng frmt = [frmt{:}]; frmt = [frmt '%s']; %# add the class atsortingbute %# read dataset fid = fopen('kddcup.data','rt'); C = textscan(fid, frmt, 'Delimiter',','); fclose(fid); %# convert nominal atsortingbutes to numeric ind = find(atsortingbNom); G = cell(numel(ind),1); for i=1:numel(ind) [C{ind(i)},G{i}] = grp2idx( C{ind(i)} ); end %# all numeric dataset M = cell2mat(C);% # convertir les attributes nominaux en numériques%# read the list of features fid = fopen('kddcup.names','rt'); C = textscan(fid, '%s %s', 'Delimiter',':', 'HeaderLines',1); fclose(fid); %# determine type of features C{2} = regexprep(C{2}, '.$',''); %# remove "." at the end atsortingbNom = [ismember(C{2},'symbolic');true]; %# nominal features %# build format ssortingng used to read/parse the actual data frmt = cell(1,numel(C{1})); frmt( ismember(C{2},'continuous') ) = {'%f'}; %# numeric features: read as number frmt( ismember(C{2},'symbolic') ) = {'%s'}; %# nominal features: read as ssortingng frmt = [frmt{:}]; frmt = [frmt '%s']; %# add the class atsortingbute %# read dataset fid = fopen('kddcup.data','rt'); C = textscan(fid, frmt, 'Delimiter',','); fclose(fid); %# convert nominal atsortingbutes to numeric ind = find(atsortingbNom); G = cell(numel(ind),1); for i=1:numel(ind) [C{ind(i)},G{i}] = grp2idx( C{ind(i)} ); end %# all numeric dataset M = cell2mat(C);ind = find (atsortingbNom);%# read the list of features fid = fopen('kddcup.names','rt'); C = textscan(fid, '%s %s', 'Delimiter',':', 'HeaderLines',1); fclose(fid); %# determine type of features C{2} = regexprep(C{2}, '.$',''); %# remove "." at the end atsortingbNom = [ismember(C{2},'symbolic');true]; %# nominal features %# build format ssortingng used to read/parse the actual data frmt = cell(1,numel(C{1})); frmt( ismember(C{2},'continuous') ) = {'%f'}; %# numeric features: read as number frmt( ismember(C{2},'symbolic') ) = {'%s'}; %# nominal features: read as ssortingng frmt = [frmt{:}]; frmt = [frmt '%s']; %# add the class atsortingbute %# read dataset fid = fopen('kddcup.data','rt'); C = textscan(fid, frmt, 'Delimiter',','); fclose(fid); %# convert nominal atsortingbutes to numeric ind = find(atsortingbNom); G = cell(numel(ind),1); for i=1:numel(ind) [C{ind(i)},G{i}] = grp2idx( C{ind(i)} ); end %# all numeric dataset M = cell2mat(C);G = cellule (numel (ind), 1);%# read the list of features fid = fopen('kddcup.names','rt'); C = textscan(fid, '%s %s', 'Delimiter',':', 'HeaderLines',1); fclose(fid); %# determine type of features C{2} = regexprep(C{2}, '.$',''); %# remove "." at the end atsortingbNom = [ismember(C{2},'symbolic');true]; %# nominal features %# build format ssortingng used to read/parse the actual data frmt = cell(1,numel(C{1})); frmt( ismember(C{2},'continuous') ) = {'%f'}; %# numeric features: read as number frmt( ismember(C{2},'symbolic') ) = {'%s'}; %# nominal features: read as ssortingng frmt = [frmt{:}]; frmt = [frmt '%s']; %# add the class atsortingbute %# read dataset fid = fopen('kddcup.data','rt'); C = textscan(fid, frmt, 'Delimiter',','); fclose(fid); %# convert nominal atsortingbutes to numeric ind = find(atsortingbNom); G = cell(numel(ind),1); for i=1:numel(ind) [C{ind(i)},G{i}] = grp2idx( C{ind(i)} ); end %# all numeric dataset M = cell2mat(C);pour i = 1: numel (ind)%# read the list of features fid = fopen('kddcup.names','rt'); C = textscan(fid, '%s %s', 'Delimiter',':', 'HeaderLines',1); fclose(fid); %# determine type of features C{2} = regexprep(C{2}, '.$',''); %# remove "." at the end atsortingbNom = [ismember(C{2},'symbolic');true]; %# nominal features %# build format ssortingng used to read/parse the actual data frmt = cell(1,numel(C{1})); frmt( ismember(C{2},'continuous') ) = {'%f'}; %# numeric features: read as number frmt( ismember(C{2},'symbolic') ) = {'%s'}; %# nominal features: read as ssortingng frmt = [frmt{:}]; frmt = [frmt '%s']; %# add the class atsortingbute %# read dataset fid = fopen('kddcup.data','rt'); C = textscan(fid, frmt, 'Delimiter',','); fclose(fid); %# convert nominal atsortingbutes to numeric ind = find(atsortingbNom); G = cell(numel(ind),1); for i=1:numel(ind) [C{ind(i)},G{i}] = grp2idx( C{ind(i)} ); end %# all numeric dataset M = cell2mat(C);[C {ind (i)}, G {i}] = grp2idx (C {ind (i)});%# read the list of features fid = fopen('kddcup.names','rt'); C = textscan(fid, '%s %s', 'Delimiter',':', 'HeaderLines',1); fclose(fid); %# determine type of features C{2} = regexprep(C{2}, '.$',''); %# remove "." at the end atsortingbNom = [ismember(C{2},'symbolic');true]; %# nominal features %# build format ssortingng used to read/parse the actual data frmt = cell(1,numel(C{1})); frmt( ismember(C{2},'continuous') ) = {'%f'}; %# numeric features: read as number frmt( ismember(C{2},'symbolic') ) = {'%s'}; %# nominal features: read as ssortingng frmt = [frmt{:}]; frmt = [frmt '%s']; %# add the class atsortingbute %# read dataset fid = fopen('kddcup.data','rt'); C = textscan(fid, frmt, 'Delimiter',','); fclose(fid); %# convert nominal atsortingbutes to numeric ind = find(atsortingbNom); G = cell(numel(ind),1); for i=1:numel(ind) [C{ind(i)},G{i}] = grp2idx( C{ind(i)} ); end %# all numeric dataset M = cell2mat(C);% # tous les sets de données numériques%# read the list of features fid = fopen('kddcup.names','rt'); C = textscan(fid, '%s %s', 'Delimiter',':', 'HeaderLines',1); fclose(fid); %# determine type of features C{2} = regexprep(C{2}, '.$',''); %# remove "." at the end atsortingbNom = [ismember(C{2},'symbolic');true]; %# nominal features %# build format ssortingng used to read/parse the actual data frmt = cell(1,numel(C{1})); frmt( ismember(C{2},'continuous') ) = {'%f'}; %# numeric features: read as number frmt( ismember(C{2},'symbolic') ) = {'%s'}; %# nominal features: read as ssortingng frmt = [frmt{:}]; frmt = [frmt '%s']; %# add the class atsortingbute %# read dataset fid = fopen('kddcup.data','rt'); C = textscan(fid, frmt, 'Delimiter',','); fclose(fid); %# convert nominal atsortingbutes to numeric ind = find(atsortingbNom); G = cell(numel(ind),1); for i=1:numel(ind) [C{ind(i)},G{i}] = grp2idx( C{ind(i)} ); end %# all numeric dataset M = cell2mat(C);
Vous pouvez également consulter la class DATASET dans la Boîte à outils des statistics.