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.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+application_train.csv filter=lfs diff=lfs merge=lfs -text

application_train.csv

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baseline_threshold.joblib

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eo_wrapper_with_proba.joblib

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fn_baseline.parquet

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fn_eo_hard.parquet

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fn_eo_opt.parquet

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fp_baseline.parquet

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fp_eo_hard.parquet

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fp_eo_opt.parquet

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lgbm_baseline.joblib

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lgbm_eg_eqodds_mitigator.joblib

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wrapper_eo.py

@@ -0,0 +1,17 @@
+import numpy as np
+
+class EOWrapper:
+    def __init__(self, mitigator, threshold):
+        self.mitigator = mitigator
+        self.threshold = threshold
+
+    def predict_proba(self, X):
+        proba_1 = np.zeros(X.shape[0])
+        for estimator, weight in zip(self.mitigator.predictors_, self.mitigator.weights_):
+            proba_1 += weight * estimator.predict_proba(X)[:, 1]
+        proba_1 = proba_1.reshape(-1)
+        return np.vstack([1 - proba_1, proba_1]).T
+
+    def predict(self, X):
+        proba_1 = self.predict_proba(X)[:, 1]
+        return (proba_1 >= self.threshold).astype(int)