%%% 清空环境变量
warning off % 关闭报警信息
close all % 关闭开启的图窗
clear % 清空变量
clc % 清空命令行
%% 读取数据
res = xlsread('数据集.xlsx');
%% 划分训练集和测试集%
P_train = res(1: 260, 1: 12)';
T_train = res(1: 260, 13)';
M = size(P_train, 2);
P_test = res(261: end, 1: 12)';
T_test = res(261: end, 13)';
N = size(P_test, 2);
f_ = size(P_train, 1); % 特征维度
num_class = length(unique(res(:, end))); % 类别数（Excel最后一列放类别）
%% 数据转置
% P_train = P_train'; P_test = P_test';
% T_train = T_train'; T_test = T_test';
%% 得到训练集和测试样本个数
M = size(P_train, 2);
N = size(P_test , 2);
%% 数据归一化
[p_train, ps_input] = mapminmax(P_train, 0, 1);
p_test = mapminmax('apply', P_test, ps_input );
t_train = T_train;
t_test = T_test ;
%% 转置以适应模型
p_train = p_train'; p_test = p_test';
t_train = t_train'; t_test = t_test';
%% 训练模型
trees = 50; % 决策树数目
leaf = 1; % 最小叶子数
%% 分类
disp(['搜索：'])
disp(['https://mbd.pub/o/DDR1'])
%% 混淆矩阵
%%if flag_conusion == 1
%% figure
%% cm = confusionchart(T_train, T_sim1);
%% cm.Title = 'Confusion Matrix for Train Data';
%% cm.ColumnSummary = 'column-normalized';
%% cm.RowSummary = 'row-normalized';
%% figure
%% cm = confusionchart(T_test, T_sim2);
%% cm.Title = 'Confusion Matrix for Test Data';
%% cm.ColumnSummary = 'column-normalized';
%% cm.RowSummary = 'row-normalized';
%%end
