From 7a9fe37b7b55a6503cf87b381e02ac243e110c97 Mon Sep 17 00:00:00 2001 From: Israel Figueroa Date: Tue, 14 Oct 2025 09:38:07 -0300 Subject: [PATCH] typo --- train.py | 1 + trainer.py | 2 +- 2 files changed, 2 insertions(+), 1 deletion(-) diff --git a/train.py b/train.py index bf29d6e..29cef13 100644 --- a/train.py +++ b/train.py @@ -30,6 +30,7 @@ seeds = [231964, 48928, 132268, 113986, 574626, 130068, 226585, 446306, 535997, # save metrics the test split for the best combinations of ML hyperparameters # * Hyperparameters GridSearch for each ML Model for up to 60 different combinations # * 10 different Machine Learning Models capable of Binary Clasification +# * Oversample training data if unbalanced # * Model trained on data with no missing values, and impute MICE and KNN # * Different random train and test splits, for given test_size ratio # A folder is created with the label name with all the state and run data diff --git a/trainer.py b/trainer.py index f772d20..322c452 100644 --- a/trainer.py +++ b/trainer.py @@ -743,7 +743,7 @@ class BinaryTuner: def wrap_and_save(self): self.logger.info("{:=^60}".format(' Saving Summary and Wrap the output in a ZipFile ')) - for metric in ["ROC_AUC", "NPV", "PPV", "Brier", "sensitivity", "specificity"]: + for metric in ["ROC_AUC", "NPV", "PPV", "Brier", "Sensitivity", "Specificity"]: with pd.ExcelWriter('{}/Summary-{}.xlsx'.format(self.name, metric) , engine='xlsxwriter') as xls: self.get_best_models(metric).to_excel(xls, sheet_name='Results')