From 5117f8276628909e02b463ed6719c5f3ac787e6a Mon Sep 17 00:00:00 2001
From: tomrink <rink@ssec.wisc.edu>
Date: Wed, 24 Apr 2024 12:26:38 -0500
Subject: [PATCH] snapshot...
---
modules/machine_learning/classification.py | 25 +++++++++++-----------
1 file changed, 12 insertions(+), 13 deletions(-)
diff --git a/modules/machine_learning/classification.py b/modules/machine_learning/classification.py
index 8607a124..035ef544 100644
--- a/modules/machine_learning/classification.py
+++ b/modules/machine_learning/classification.py
@@ -60,12 +60,12 @@ def logistic_regression(x, y):
yhat_prob = LR.predict_proba(x_test)
print(confusion_matrix(y_test, yhat, labels=[1,0]))
- print('Accuracy: ', accuracy_score(y_test, yhat))
- print('Jaccard Idx: ', jaccard_score(y_test, yhat))
- print('Precision: ', precision_score(y_test, yhat))
- print('Recall: ', recall_score(y_test, yhat))
- print('F1: ', f1_score(y_test, yhat))
- print('AUC: ', roc_auc_score(y_test, yhat_prob[:, 1]))
+ print('Accuracy: ', "{:.4f}".format(accuracy_score(y_test, yhat)))
+ print('Jaccard Idx: ', "{:.4f}".format(jaccard_score(y_test, yhat)))
+ print('Precision: ', "{:.4f}".format(precision_score(y_test, yhat)))
+ print('Recall: ', "{:.4f}".format(recall_score(y_test, yhat)))
+ print('F1: ', "{:.4f}".format(f1_score(y_test, yhat)))
+ print('AUC: ', "{:.4f}".format(roc_auc_score(y_test, yhat_prob[:, 1])))
def k_nearest_neighbors(x, y, k=4):
@@ -82,10 +82,9 @@ def k_nearest_neighbors(x, y, k=4):
yhat = KN_C.predict(x_test)
yhat_prob = KN_C.predict_proba(x_test)
- print(confusion_matrix(y_test, yhat, labels=[1,0]))
- print('Accuracy: ', accuracy_score(y_test, yhat))
- print('Jaccard Idx: ', jaccard_score(y_test, yhat))
- print('Precision: ', precision_score(y_test, yhat))
- print('Recall: ', recall_score(y_test, yhat))
- print('F1: ', f1_score(y_test, yhat))
- print('AUC: ', roc_auc_score(y_test, yhat_prob[:, 1]))
\ No newline at end of file
+ print('Accuracy: ', "{:.4f}".format(accuracy_score(y_test, yhat)))
+ print('Jaccard Idx: ', "{:.4f}".format(jaccard_score(y_test, yhat)))
+ print('Precision: ', "{:.4f}".format(precision_score(y_test, yhat)))
+ print('Recall: ', "{:.4f}".format(recall_score(y_test, yhat)))
+ print('F1: ', "{:.4f}".format(f1_score(y_test, yhat)))
+ print('AUC: ', "{:.4f}".format(roc_auc_score(y_test, yhat_prob[:, 1])))
\ No newline at end of file
--
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