# Train a knn model where k is 3 using the training dataset.

Posted: February 26th, 2022

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Question 11

Train a knn model where k is 3 using the training dataset.

Make predictions using the test dataset

Compute accuracy and save as accuracy

Hints:

You need to use the KNeighborsClassifier function. Instantiate a knn object and pass the number of neighbors to the function. Train the model using the X_train and y_train. Then make predictions using X_test. Then compute the accuracy using the predicted values and y_test.

Check Module 6d: Model Performance and _Module 5c: Classification

Question 12

Train a Random Forests model where the number of estimators is 100 using the training dataset.

Make predictions using the test dataset

Compute accuracy and save as accuracy

Hints:

You need to use the RandomForestClassifier function. Instantiate a RandomForestClassifier object and pass the number of estimators to the function. Train the model using the X_train and y_train. Then make predictions using X_test. Then compute the accuracy using the predicted values and y_test.

Check Module 6d: Model Performance and _Module 5c: Classification

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