code_3.rar_gender matlab_交叉验证_折交叉验证_预测性别_预测用户性别

function [err_gen err_age t_train t_test] = cross_validation(movies, ratings, users) users0 = users(1:604,:); users1 = users(605:1208,:); users2 = users(1209:1812,:); users3 = users(1813:2416,:); users4 = users(2417:3020,:); users5 = users(3021:3624,:); users6 = users(3625:4228,:); users7 = users(4229:4832,:); users8 = users(4833:5436,:); users9 = users(5437:6040,:); err_gen = zeros(10,1); err_age = zeros(10,1); t_train = zeros(10,1); t_test = zeros(10,1); [err_gen(1) err_age(1) t_train(1) t_test(1)] = predict( movies, [users1;users2;users3;users4;users5;users6;users7;users8;users9], ratings, users0); [err_gen(2) err_age(2) t_train(2) t_test(2)] = predict( movies, [users0;users2;users3;users4;users5;users6;users7;users8;users9], ratings, users1); [err_gen(3) err_age(3) t_train(3) t_test(3)] = predict( movies, [users0;users1;users3;users4;users5;users6;users7;users8;users9], ratings, users2); [err_gen(4) err_age(4) t_train(4) t_test(4)] = predict( movies, [users0;users1;users2;users4;users5;users6;users7;users8;users9], ratings, users3); [err_gen(5) err_age(5) t_train(5) t_test(5)] = predict( movies, [users0;users1;users2;users3;users5;users6;users7;users8;users9], ratings, users4); [err_gen(6) err_age(6) t_train(6) t_test(6)] = predict( movies, [users0;users1;users2;users3;users4;users6;users7;users8;users9], ratings, users5); [err_gen(7) err_age(7) t_train(7) t_test(7)] = predict( movies, [users0;users1;users2;users3;users4;users5;users7;users8;users9], ratings, users6); [err_gen(8) err_age(8) t_train(8) t_test(8)] = predict( movies, [users0;users1;users2;users3;users4;users5;users6;users8;users9], ratings, users7); [err_gen(9) err_age(9) t_train(9) t_test(9)] = predict( movies, [users0;users1;users2;users3;users4;users5;users6;users7;users9], ratings, users8); [err_gen(10) err_age(10) t_train(10) t_test(10)] = predict( movies, [users0;users1;users2;users3;users4;users5;users6;users7;users8], ratings, users9); end