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Run experiments tuning random forest params #83

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Run experiments tuning random forest params #83

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dberenbaum
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Better RF split and number of estimators based on small grid search.

@shcheklein

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CML Report

Plots

ROC
Precision-Recall
Confusion Matrix

Feature Importance: main

Feature Importance: main

Feature Importance: workspace

Feature Importance: workspace

Metrics and Params

main → workspace

Path Metric main workspace Change
eval/metrics.json avg_prec.test 0.925 0.92688 0.0018818
eval/metrics.json avg_prec.train 0.97437 0.99932 0.024952
eval/metrics.json roc_auc.test 0.94602 0.94509 -0.00092798
eval/metrics.json roc_auc.train 0.98667 0.99971 0.013041
Path Param main workspace Change
params.yaml train.min_split 0.01 8 7.99
params.yaml train.n_est 50 100 50

@samran5 samran5 mentioned this pull request Oct 25, 2024
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@iterative iterative deleted a comment from samran5 Oct 25, 2024
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@dberenbaum @shcheklein