codecov-commenter
commented
2 years ago Codecov Report
Merging #130 (50f5572) into dev (5bb7c6d) will decrease coverage by
1.42%. The diff coverage is66.66%.
@@ Coverage Diff @@
## dev #130 +/- ##
==========================================
- Coverage 96.07% 94.64% -1.43%
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Files 21 20 -1
Lines 866 878 +12
==========================================
- Hits 832 831 -1
- Misses 34 47 +13 | Impacted Files | Coverage Δ | |
|---|---|---|
| src/mlj/interface.jl | 81.03% <66.66%> (-7.68%) |
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| src/mlj/classifiers.jl | 50.00% <0.00%> (-50.00%) |
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| src/mlj/regressors.jl | 6.66% <0.00%> (-49.59%) |
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| src/fit/iwls.jl | 100.00% <0.00%> (ø) |
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| src/glr/d_l2loss.jl | 100.00% <0.00%> (ø) |
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| src/glr/d_robust.jl | 100.00% <0.00%> (ø) |
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| src/glr/d_logistic.jl | 100.00% <0.00%> (ø) |
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| src/loss-penalty/standard.jl | 100.00% <0.00%> (ø) |
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| src/MLJLinearModels.jl | ||
| ... and 3 more |
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PR #123 makes an explicit distinction between two cases:
The way these things are processed is not the same. In short, the output of LC is a score corresponding to "class 1" (whatever it is), the score comes out of sigmoid (logic), whereas in the MN case it comes out of a softmax.
Anyway long story short, the PR #123 was not properly finished (the
MLJ.fitwas fixed correctly but theMLJ.predictshould have been fixed in basically the same way.