mixed dictionary results improved significantly with nest 100 + lr 0.5

AIclassifier.py

@@ -265,7 +265,7 @@ def create_vectors_list(sents, conversion_dict):
 #params = {'activation': 'relu', 'hidden_layer_sizes': (200, 250, 200), 'learning_rate': 'adaptive', 'learning_rate_init': 0.001, 'max_iter': 5200, 'solver': 'adam'}
 
 
-adaclassifier = AdaBoostClassifier(n_estimators=50, learning_rate=1)
+adaclassifier = AdaBoostClassifier(n_estimators=100, learning_rate=0.5)
 #svc_classifier = make_pipeline(StandardScaler(), OneVsRestClassifier(LinearSVC(dual=False,random_state=None, tol=1e-5, C=1)))
 #svc_classifier = make_pipeline(StandardScaler(), OneVsOneClassifier(LinearSVC(dual=False,random_state=None, tol=1e-5, C=1)))
 #mlp_classifier = MLPClassifier( max_iter=300, early_stopping=True, hidden_layer_sizes=300, batch_size=32) # random_state=1111111,

features.txt

@@ -17,6 +17,16 @@ should
 safer
 believe
 express
+experience
+can
+no
+connect
+they
+public
+example
+cookies
+content
+and
 to be
 you should
 to enable
@@ -28,3 +38,6 @@ when people
 provide you
 and protect
 you can
+have a
+you with
+with the

output/AI Classifier/1labelPredictionsStatsTest.txt

@@ -2,13 +2,13 @@ Performance measures - Mixed Dictionary - Adaboost
 
 Test set:
 
-Precision macro: 0.246
-Precision Individually: [0.364 0.    0.615 0.    0.25 ]
-Recall macro: 0.289
-Recall Individually: [0.571 0.    0.774 0.    0.1  ]
-F1 Score micro: 0.493
-F1 Score macro: 0.255
-F1 Score weighted: 0.431
-F1 Score Individually: [0.444 0.    0.686 0.    0.143]
+Precision macro: 0.333
+Precision Individually: [0.5   0.    0.58  0.25  0.333]
+Recall macro: 0.297
+Recall Individually: [0.357 0.    0.935 0.091 0.1  ]
+F1 Score micro: 0.537
+F1 Score macro: 0.284
+F1 Score weighted: 0.463
+F1 Score Individually: [0.417 0.    0.716 0.133 0.154]