From 1a99bf702be41a3b707d0e67226c20e79421b713 Mon Sep 17 00:00:00 2001
From: Khalleud <ledk14@gmail.com>
Date: Mon, 7 Jun 2021 18:04:44 +0200
Subject: [PATCH] [FIX] update report output from text to csv
---
classifiers.py | 2 --
experimentsClassicClassifiers.py | 2 +-
2 files changed, 1 insertion(+), 3 deletions(-)
diff --git a/classifiers.py b/classifiers.py
index 96e90ab..16db401 100644
--- a/classifiers.py
+++ b/classifiers.py
@@ -22,8 +22,6 @@ classifiers = [
param_grid_svm = {'C':[1,10,100,1000],'gamma':[1,0.1,0.001,0.0001], 'kernel':['linear','rbf']}
-#param_grid_svm = {'C':[1,10],'gamma':[1], 'kernel':['linear','rbf']}
-#param_grid_svm = [{'kernel': ['rbf'], 'gamma': [1e-3, 1e-4], 'C': [1, 10, 100, 1000]}, {'kernel': ['linear'], 'C': [1, 10, 100, 1000]}]
param_grid_decisionTree = { 'criterion' : ['gini', 'entropy'], 'max_depth':range(5,10), 'min_samples_split': range(5,10), 'min_samples_leaf': range(1,5) }
param_grid_rfc = { 'n_estimators': [200, 500], 'max_features': ['auto', 'sqrt', 'log2'], 'max_depth' : [4,5,6,7,8], 'criterion' :['gini', 'entropy'] }
param_grid_lr = {"C":np.logspace(-3,3,7), "penalty":["l1","l2"]}
diff --git a/experimentsClassicClassifiers.py b/experimentsClassicClassifiers.py
index 091a4ef..958752e 100644
--- a/experimentsClassicClassifiers.py
+++ b/experimentsClassicClassifiers.py
@@ -143,10 +143,10 @@ for columnInput in [columnText, 'firstParagraph']:
file_name_report = columnInput + '_' +feature_technique_name + '_' + clf_name
report, accuracy, weighted_avg = evaluate_model(clf, test_x, valid_y, y_pred, valid_y, [str(e) for e in encoder.transform(encoder.classes_)], encoder.classes_, os.path.join('reports', columnClass, dir_name_report, file_name_report)+'.pdf')
+ report.to_csv(os.path.join('reports', columnClass, dir_name_report, file_name_report+'.csv'))
with open(os.path.join('reports', columnClass, dir_name_report, file_name_report+'.txt'), 'w') as f:
sys.stdout = f # Change the standard output to the file we created.
- print(report)
print('accuracy : {}'.format(accuracy))
print('weighted_Precision : {}'.format(weighted_avg['precision']))
print('weighted_Recall : {}'.format(weighted_avg['recall']))
--
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