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[Outreachy applications] Visualization for misclassifications #7

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dzeber opened this issue Mar 4, 2020 · 6 comments · Fixed by #23 or #59
Closed

[Outreachy applications] Visualization for misclassifications #7

dzeber opened this issue Mar 4, 2020 · 6 comments · Fixed by #23 or #59
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good first issue Good for newcomers

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@dzeber
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dzeber commented Mar 4, 2020

Misclassifications can reveal a lot about the boundaries of performance of a classifier. Develop a visualization that helps dig into misclassified datapoints in the test set. A simple approach for a binary classifier would be to plot a histogram of the predicted class probabilities across the misclassified test samples in each class.

@dzeber dzeber added the good first issue Good for newcomers label Mar 5, 2020
@KaairaGupta
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This issue seems interesting. May I be assigned this?

@dzeber
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dzeber commented Mar 5, 2020

You're welcome to work on it and submit a contribution! We're not assigning issues currently to allow people to bring multiple perspectives or approaches to these questions.

@shristi428
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how can we contribute in the project should we PR then you assign us task ?

@dzeber
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dzeber commented Mar 6, 2020

@shristi428 You can submit a PR referencing the issue you worked on.

@namrathagopalabhatla
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Hey @dzeber! What dataset do we use to test out our code?

@dzeber
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dzeber commented Mar 14, 2020

@namrathagopalabhatla whichever you like. It might be a good start to use the same data & model you used for #2.

KaairaGupta added a commit to KaairaGupta/PRESC that referenced this issue Mar 16, 2020
mlopatka pushed a commit that referenced this issue Mar 19, 2020
…of classes (#86)

* Contribution to issue #2

* Eliminació de l'arxiu de prova

* Eliminació de l'arxiu de prova

* Fixed axes when not numbers and removed superfluous function.

* Initial commit to Issue #7 Visualization of missclassifications.

* Adding explanatory graphs for the notebook regarding Issue #7

* Better graph to illustrate option 'hits-fails'.
mlopatka pushed a commit that referenced this issue Mar 20, 2020
* adds a module to visualize misclassification and tests it on winequality.csv

* adds description and details for results obtained
@mlopatka mlopatka reopened this Mar 20, 2020
@mlopatka mlopatka reopened this Mar 20, 2020
mlopatka pushed a commit that referenced this issue Apr 8, 2020
* #7 Visualization for misclassification

* Comparing test sample classifications between models

I compared the random forest and k nearest neighbors classifier models and used a barchart to visualize the classification of the test set

* added probability to misclasification visualization

* new misclassification visualization method used

* moved into misclassification_visualization folder

* moved to misclassification visualization folder

* Traversal of the space of train-test splits

* fixed file path and did better visualization

* Update #7 visualization for misclassifications.ipynb

* Update misclassification_function.py

* made changes to #7

* Delete Traversal of the space of train-test splits #3.ipynb

* Delete traversal_function.py

* Traversal of the space of train-test splits #3
@dzeber dzeber changed the title Visualization for misclassifications [Outreachy applications] Visualization for misclassifications Jul 14, 2020
@dzeber dzeber closed this as completed Jul 14, 2020
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