Relation between using stratify and class weights for imbalanced classes
$begingroup$
I'm working on a multi-class classification problem where the classes are imbalanced (70:25:5).
Train-Test Split
x_train, x_test, y_train, y_test = train_test_split(X, Y, test_size=0.2, random_state=42, stratify=Y)
Random Forest Classifier
cls = {0:.9, 1:.09, 3:.01}
RandomForestClassifier(n_estimators=100, n_jobs=-1, random_state=42, oob_score=True, class_weight=cls)
I do not see a change in the results after assigning class weights. Is there anything that I need to look into in particular here? Thanks in advance!
random-forest multiclass-classification unbalanced-classes sampling
asked 8 mins ago
Van PeerVan Peer
103117
$endgroup$
add a comment |
$begingroup$
I'm working on a multi-class classification problem where the classes are imbalanced (70:25:5).
Train-Test Split
x_train, x_test, y_train, y_test = train_test_split(X, Y, test_size=0.2, random_state=42, stratify=Y)
Random Forest Classifier
cls = {0:.9, 1:.09, 3:.01}
RandomForestClassifier(n_estimators=100, n_jobs=-1, random_state=42, oob_score=True, class_weight=cls)
I do not see a change in the results after assigning class weights. Is there anything that I need to look into in particular here? Thanks in advance!
random-forest multiclass-classification unbalanced-classes sampling
asked 8 mins ago
Van PeerVan Peer
103117
$endgroup$
add a comment |
$begingroup$
I'm working on a multi-class classification problem where the classes are imbalanced (70:25:5).
Train-Test Split
x_train, x_test, y_train, y_test = train_test_split(X, Y, test_size=0.2, random_state=42, stratify=Y)
Random Forest Classifier
cls = {0:.9, 1:.09, 3:.01}
RandomForestClassifier(n_estimators=100, n_jobs=-1, random_state=42, oob_score=True, class_weight=cls)
I do not see a change in the results after assigning class weights. Is there anything that I need to look into in particular here? Thanks in advance!
random-forest multiclass-classification unbalanced-classes sampling
asked 8 mins ago
Van PeerVan Peer
103117
$endgroup$
I'm working on a multi-class classification problem where the classes are imbalanced (70:25:5).
Train-Test Split
x_train, x_test, y_train, y_test = train_test_split(X, Y, test_size=0.2, random_state=42, stratify=Y)
Random Forest Classifier
cls = {0:.9, 1:.09, 3:.01}
RandomForestClassifier(n_estimators=100, n_jobs=-1, random_state=42, oob_score=True, class_weight=cls)
I do not see a change in the results after assigning class weights. Is there anything that I need to look into in particular here? Thanks in advance!
random-forest multiclass-classification unbalanced-classes sampling
random-forest multiclass-classification unbalanced-classes sampling
asked 8 mins ago
Van PeerVan Peer
103117
asked 8 mins ago
Van PeerVan Peer
103117
asked 8 mins ago
Van PeerVan Peer
103117
asked 8 mins ago
Van PeerVan Peer
103117
asked 8 mins ago
Van PeerVan Peer
103117
103117
add a comment |
add a comment |
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