LASSO function not behaving as expected
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I've been performing LASSO regulerisation but it has been behaving oddly. Code that once works no longer is, and now I can't even get the example from Matlab help to work. For instance here's some data:
rng default % For reproducibility
X = randn(100,5);
weights = [0;2;0;-3;0]; % Only two nonzero coefficients
y = X*weights + randn(100,1)*0.1; % Small added noise
Following he documentation verbatim,
B = lasso(X,y);
B(:,25)
returns the error:
Index in position 2 exceeds array bounds (must not exceed 6).
because when I run it the results are:
B =
0 0 0 0 -0.0067 -0.0067
0 0 1.9802 1.9838 1.9919 1.9920
0 0 0 -0.0039 -0.0109 -0.0109
0 -0.6818 -2.9817 -2.9865 -2.9958 -2.9959
0 0 0 0 0 0.0001
So is the documentation incorrect or is something else going on here?
Additionally, the function doesn't seem to accept values for lambda, for example:
B = lasso(X,y)
C = lasso(X,y,'Lambda', 0.18)
D = lasso(X,y,'Lambda',linspace(0,1))
gives:
B =
0 0 0 0 -0.0067 -0.0067
0 0 1.9802 1.9838 1.9919 1.9920
0 0 0 -0.0039 -0.0109 -0.0109
0 -0.6818 -2.9817 -2.9865 -2.9958 -2.9959
0 0 0 0 0 0.0001
C =
0 0 0 0 -0.0067 -0.0067
0 0 1.9802 1.9838 1.9919 1.9920
0 0 0 -0.0039 -0.0109 -0.0109
0 -0.6818 -2.9817 -2.9865 -2.9958 -2.9959
0 0 0 0 0 0.0001
Operands to the || and && operators must be convertible to logical scalar values.
Error in larsen (line 197)
if storepath && size(b,2) > step
Error in lasso (line 119)
[b steps] = larsen(X, y, 0, stop, Gram, storepath, verbose);
C is returning an identical result despite a single value for lambda being given. And why is D producing an error - especially when this is the syntax given in the LASSO help page.
Any pointers would be appreciated.
2 件のコメント
Image Analyst
2021 年 1 月 19 日
Give us the code, in a single snippet, that runs and gives the error, because this:
rng default % For reproducibility
X = randn(100,5);
weights = [0;2;0;-3;0]; % Only two nonzero coefficients
y = X*weights + randn(100,1)*0.1; % Small added noise
B = lasso(X,y);
B(:,25)
runs without any error at all in R2020b.
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