What is cold start problem in classification systems?

Cold start refers to difficulty in making accurate predictions when little or no historical data is available.

Cold start problems occur in recommendation and classification systems when new users, items, or environments lack historical data. Solutions include using content-based features, transfer learning, or default priors. Hybrid systems combine collaborative and content-based signals to mitigate this issue.