0
>> for i=1:10;
v(i) = 2^i;
end;
>> v
v =
2
4
8
16
32
64
128
256
512
1024
>> indices = 1:10;
>> indices
indices =
Columns 1 through 9
1 2 3 4 5 6 7 8 9
Column 10
10
>> for i = indices,
disp(i);
end;
1
2
3
4
5
6
7
8
9
10
>> v
v =
2
4
8
16
32
64
128
256
512
1024
>> i = 1;
>> while i<=5,
v(i) = 100
i=i+1
end;
>> v
v =
100
100
100
100
100
64
128
256
512
1024
>> i = 1;
>> while true,
v(i) = 999;
i = i+1
if i == 6,
break;
end;
end;
>> v
v =
999
999
999
999
999
64
128
256
512
1024
>>if ****,
######;
elseif ****,
#######;
else,
######;
end;
=============================================================
拟合上图训练集合
>> x = [1 1; 1 2; 1 3]
>>y = [1; 2; 3]
>>theta = [0;1]
function J = costFunctionJ(X, y, thera)
% X is the "design matrix" containing our training examples,
%y is the class labels
m = size(X, 1) %number of training examples
predictions = X*thera; % predictions of hypothesis on all m examples
sqrErrors = (predictions - y).^2;
J = 1/(2*m) *sum(sqrErrors);