How can I adjust the classification threshold in my model?

How can I adjust the classification threshold in my model?

You can adjust the classification threshold by changing the probability cutoff for classifying instances. What model are you using?

I'm using a logistic regression model.

For logistic regression, you can set the threshold using the predict_proba method. Would you like a code example?

Yes, please provide a code example.

Sure! Here's a simple example in Python:

from sklearn.linear_model import LogisticRegression

model = LogisticRegression()
model.fit(X_train, y_train)

# Get predicted probabilities
probs = model.predict_proba(X_test)[:, 1]

# Set your threshold
threshold = 0.6
predictions = (probs >= threshold).astype(int)