clear all;
clc;
winsize=5;
%% 資料讀入
[num,s]
=xlsread
("****");
time=s(
2:size
(s,1),
1);dt =
datetime
(time,
'inputformat'
,'yyyy/mm/dd hh:mm:ss');
for i =1:
size
(dt)if(
isnat(dt
(i)))dt
(i)=
datetime
(time
(i),
'format'
,'yyyy/mm/dd 00:00:00');
endenddtnum =
datenum
(dt)
; data =
zeros
(size
(dtnum,1)
,5);
data(:
,1)= dtnum;
%時間data(:
,2)=
num(:,
1);data(:
,3)=
num(:,
2);%h1
data(:
,4)=
num(:,
3);%h2
data(:
,5)=
num(:,
4);%h3
%% 劃分訓練集和測試集
a =randperm
(size
(dtnum,1)
);splitrate =
0.7;
%劃分比例
splitindex =
floor
(splitrate*
size
(dtnum,1)
);%劃分索引
train =
data(a
(1:splitindex),:
);test =
data(a
((splitindex+1)
:end),:
);i_train =
train(:
,1:2
);o_train_h1 =
train(:
,3);
o_train_h2 =
train(:
,4);
o_train_h3 =
train(:
,5);
% i_test =
test(:
,1:2
);% o_test_h1 =
test(:
,3);
% o_test_h2 =
test(:
,4);
% o_test_h3 =
test(:
,5);
%% h1 訓練及**
step =1;
tree_num=
500;
%樹的數目
for i=
1:step
model=
regrf_train
(i_train ,o_train_h1,tree_num)
; y_hat1 =
regrf_predict
(data(:
,1:2
), model)
;end
% 誤差
err1=
(y_hat1-
data(:
,3))
./data(:
,3);
y_hat11=
filter
(ones(1
,winsize)
/winsize,1,
[y_hat1;
zeros
(floor
(winsize/2)
,1)]
);y_hat1=
y_hat11
(round
(winsize/2)
:end);%
% h2 訓練及**
for i=
1:step
mode2=
regrf_train
(i_train ,o_train_h2,tree_num)
; y_hat2 =
regrf_predict
(data(:
,1:2
), mode2)
;end
% 誤差
err2=
(y_hat2-
data(:
,4))
./data(:
,4);
y_hat22=
filter
(ones(1
,winsize)
/winsize,1,
[y_hat2;
zeros
(floor
(winsize/2)
,1)]
);y_hat2=
y_hat22
(round
(winsize/2)
:end);%
% h3 訓練及**
for i=
1:step
mode3=
regrf_train
(i_train ,o_train_h3,tree_num)
; y_hat3 =
regrf_predict
(data(:
,1:2
), mode3)
;end
% 誤差
err3=
(y_hat3-
data(:
,5))
./data(:
,5);
y_hat33=
filter
(ones(1
,winsize)
/winsize,1,
[y_hat3;
zeros
(floor
(winsize/2)
,1)]
);y_hat3=
y_hat33
(round
(winsize/2)
:end);%
% 評價指
h1_r2 =1-
norm
(data(:
,3)-y_hat1)^2
/norm
(data(:
,3)-
mean
(data(:
,3))
)^2h2_r2 =1-
norm
(data(:
,4)-y_hat2)^2
/norm
(data(:
,4)-
mean
(data(:
,4))
)^2h3_r2 =1-
norm
(data(:
,5)-y_hat3)^2
/norm
(data(:
,5)-
mean
(data(:
,5))
)^2
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