Closed janezd closed 2 years ago
Merging #139 (bfe3c4d) into master (eb35826) will decrease coverage by
0.50%
. The diff coverage is96.42%
.
@@ Coverage Diff @@
## master #139 +/- ##
==========================================
- Coverage 82.85% 82.35% -0.51%
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Files 17 17
Lines 3015 3054 +39
Branches 420 425 +5
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+ Hits 2498 2515 +17
- Misses 463 481 +18
- Partials 54 58 +4
Impacted Files | Coverage Ξ | |
---|---|---|
.../educational/widgets/owpolynomialclassification.py | 88.45% <96.42%> (+0.77%) |
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orangecontrib/educational/widgets/owkmeans.py | 76.54% <0.00%> (-3.81%) |
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...gecontrib/educational/widgets/owgradientdescent.py | 88.16% <0.00%> (+0.23%) |
:arrow_up: |
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I'm changing this back into draft: in training, the widget treats the data instances without class as instances of non-target class. Try https://ucilnica.fri.uni-lj.si/mod/resource/view.php?id=48556 and see how the line moves when changing the target class.
Ready now.
The problem with missing values is fixed primarily in https://github.com/biolab/orange3/pull/5891.
It looks good. I think it also needs to be included in the documentation. Still, since the documentation is outdated already (not only because of this PR), I will merge this PR and open an issue to remind us to update the documentation.
Issue
Resolves #134.
Description of changes
At one point (presumably #112) somebody (presumanbly I) decided to expose that polynomial classifier classifies the target class vs. others by showing other classes as gray. At some point in one lecture, this started bothering me - I wanted to see both, actual and predicted classes.
This PR thus backtracks somewhat. At the same time it allows for observing/comparing the actual classes and predictions by showing the actual class with pen and the prediction with brush (with transparency corresponding to probability).
The background still shows the target color vs. gray to emphasize that the model predicts the target (e.g. the two classes are not symmetric - yes, mathematically, but not when we discuss it in class).
When predicting a binary class, the brush of the other class matches its color. When predicting multiple classes, the brush for others is gray. See the two images below.
Includes