[WIP] Add easy model fitting and comparison #77
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geoalgo
reviewed
Sep 20, 2024
| @@ -532,3 +536,100 @@ def _convert_binary_to_multiclass(self, predictions: np.ndarray, dataset: str) - | |||
| return np.stack([1 - predictions, predictions], axis=predictions.ndim) | |||
| else: | |||
| return predictions | |||
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| def _convert_time_infer_s_from_sample_to_batch(self, df: pd.DataFrame): | |||
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Can we move those functions to an util? Those are very specific function regarding to one analysis, if we all our utils in AbstractRepository, it will be very hard to maintain.
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Yeah, a lot of this code is currently WIP. Basically, we are prioritizing making it work first, and then once it works we will do clean up
| """ | ||
| Class to Fetch Train Test Splits of context dataset | ||
| """ | ||
| def get_context_train_test_split(self, repo: EvaluationRepository, task_id: Union[int, List[int]], repeat: int = 0, |
prateekdesai04
commented
Oct 3, 2024
| from sklearn.utils.multiclass import unique_labels | ||
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| class TabForestPFN_sklearn(BaseEstimator, ClassifierMixin): |
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Have not touched this class as it still seems to be a WIP
Innixma
changed the title
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Description of changes:
This PR adds plotting functionality comparing the TabRepo configs vs AG fitted models.
Following are the changes compared to the earlier PR, i.e., : #76
The
convert_leaderboard_to_configs()is modified and cleaned up, the earlier one renamed columns which were not present in the DataFrame.Addition of
plot_overall_rank_comparison()which plots various figures for all the models in the DataFrame i.e., (fitted models + TabRepo configs)NOTE that in the earlier #76, there is a fold mismatch in purpose to test the functionality of
compare_metrics(), but in this PRtemp_script.pyhas the same folds for both fitted models and TabRepo configs, this is done just to keep the folds same while plotting.The plot function breaks when ELO figures are plotted and the code will give an error, still a WIP, but rest of the plots can be found in
initial_experiment/output/figures, the code runs up-to that mark.By submitting this pull request, I confirm that you can use, modify, copy, and redistribute this contribution, under the terms of your choice.