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Sorting out issue with calling predict on matrix #219

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merged 13 commits into from
Apr 24, 2023
Merged

Sorting out issue with calling predict on matrix #219

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bac03b7
removed changes related to other PR and added reformat function
pat-alt Mar 30, 2023
08316cb
fit! method through an error because matrix wasn't transposed
pat-alt Mar 30, 2023
221bc58
first go at completing remaining tasks.
pat-alt Apr 5, 2023
3c36915
currently a little clueless about this error
pat-alt Apr 5, 2023
e98182a
tests now passing
pat-alt Apr 7, 2023
0ca1d43
updated docstrings
pat-alt Apr 7, 2023
d01f536
fixed scitype warning
pat-alt Apr 12, 2023
d3942ec
test is failing
pat-alt Apr 17, 2023
f5c6b50
tests passing
pat-alt Apr 18, 2023
aa5c6ab
Update src/regressor.jl
pat-alt Apr 22, 2023
56eec63
collate function
pat-alt Apr 22, 2023
cefd9f3
tests passing
pat-alt Apr 22, 2023
49d11af
removed a redundant print statement
pat-alt Apr 23, 2023
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1 change: 1 addition & 0 deletions src/core.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -224,6 +224,7 @@ by `model.batch_size`.)

"""
function collate(model, X, y)
y = y isa Matrix ? Tables.table(y) : y
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I'm trying to understand why this fix was needed. The nrows function is supposed to work for matrices as well as tables:

using MLJBase
julia> y = rand(2, 6)
julia> nrows(y)
2

julia> nrows(y')
6

And line 230 below should already take care of the conversion of y to a matrix, no?

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This was giving me an error previously, because the nrows method defined in the same file expects a table (or else it throws an ArgumentError. I've adjusted that and tests are passing.

row_batches = Base.Iterators.partition(1:nrows(y), model.batch_size)
Xmatrix = reformat(X)
ymatrix = reformat(y)
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