How do I implement class weights in Scikit-Learn?

How do I implement class weights in Scikit-Learn?

You can implement class weights in Scikit-Learn by using the class_weight parameter in classifiers like LogisticRegression or RandomForestClassifier. You can set it to 'balanced' or provide a dictionary mapping class labels to weights.

Can you show me an example of how to do that?

Sure! Here's a simple example:

from sklearn.ensemble import RandomForestClassifier
from sklearn.datasets import make_classification

X, y = make_classification(n_classes=3, weights=[0.1, 0.3, 0.6])
clf = RandomForestClassifier(class_weight='balanced')
clf.fit(X, y)

What if I want to specify custom weights?

You can specify custom weights by passing a dictionary to the class_weight parameter. For example:

class_weights = {0: 1, 1: 2, 2: 3}
clf = RandomForestClassifier(class_weight=class_weights)

Are there any other classifiers that support class weights?

Yes, many classifiers in Scikit-Learn support class weights, including SVC, LogisticRegression, and GradientBoostingClassifier. Always check the documentation for details.