Handling Class Imbalance in Classification

Scenario

You are training a binary classifier and discover that the positive class is much rarer than the negative class. A model with high accuracy may still miss most of the cases you care about.

Question

How would you handle class imbalance in a dataset?

Problem

Scenario

You are training a binary classifier and discover that the positive class is much rarer than the negative class. A model with high accuracy may still miss most of the cases you care about.

Question

How would you handle class imbalance in a dataset?

Example Dataset

Size·120K rows, 38 featuresTarget·Rare binary eventClass balance·4.5% positiveFeature types·Mixed numerical and categorical

Problem

Scenario

You are training a binary classifier and discover that the positive class is much rarer than the negative class. A model with high accuracy may still miss most of the cases you care about.

Question

How would you handle class imbalance in a dataset?

Example Dataset

Size·120K rows, 38 featuresTarget·Rare binary eventClass balance·4.5% positiveFeature types·Mixed numerical and categorical

Problem

Scenario

You are training a binary classifier and discover that the positive class is much rarer than the negative class. A model with high accuracy may still miss most of the cases you care about.

Question

How would you handle class imbalance in a dataset?

Example Dataset

Size·120K rows, 38 featuresTarget·Rare binary eventClass balance·4.5% positiveFeature types·Mixed numerical and categorical

Interview Guides

Problem

Scenario

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Example Dataset

Problem

Scenario

Question

Example Dataset

Handling Class Imbalance in Classification

Problem

Scenario

Question

Example Dataset

Problem

Scenario

Question

Example Dataset