Classification with Costly Features

The task of Classification with Costly Features aims to classify datasets that contain high-cost features by evaluating performance under different budget settings, optimizing resource allocation and classification outcomes. This task uses the area under the normalized cost-accuracy curve as the ultimate evaluation metric, ensuring optimal classification results with limited resources, which holds significant practical value.