Decision Tree Comparison
Let's now explore another model in our analysis. We will compare the results obtained with the Logistic Regression algorithm to those from the DecisionTreeClassifier. The pipeline will remain the same as in the previous chapter.
The key takeaway here is that in the world of Data Science, it is crucial to continuously try different approaches that may yield better results on your data.
Завдання
Swipe to start coding
- Initialize the
DecisionTreeClassifiermodel. - Train the model.
- Make predictions on the test set.
- Use the appropriate method to evaluate the model (compute accuracy score).
Рішення
from sklearn.tree import DecisionTreeClassifier
# Initialize the model
dt = DecisionTreeClassifier()
# Train the model
dt.fit(X_train, y_train)
# Make predictions
pred_dt = dt.predict(X_test)
# Evaluate the model (accuracy score)
dt.score(X_test, y_test) # This model performs better
Mark tasks as Completed
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