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confusion matrix for classification

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josh.ipynb answered on June 7, 2022 Popularity 10/10 Helpfulness 4/10

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answer confusion matrix for classification

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# Import necessary modules
from sklearn.metrics import classification_report
from sklearn.metrics import confusion_matrix

# Create training and test set
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.4, random_state=42)

# Instantiate a k-NN classifier: knn
knn = KNeighborsClassifier(n_neighbors=6)

# Fit the classifier to the training data
knn.fit(X_train, y_train)

# Predict the labels of the test data: y_pred
y_pred = knn.predict(X_test)

# Generate the confusion matrix and classification report
print(confusion_matrix(y_test, y_pred))
print(classification_report(y_test, y_pred))

Popularity 10/10 Helpfulness 4/10 Language python

Source: campus.datacamp.com

Tags: classification confusion-matrix python

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josh.ipynb

Contributed on Jun 07 2022

josh.ipynb

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