Classification with Costly Features

4 papers with code • 0 benchmarks • 0 datasets

The task is to classify the dataset with costly features with different budget settings. The final metric is the normalized area under the cost-accuracy curve.

Most implemented papers

Classification with Costly Features as a Sequential Decision-Making Problem

jaromiru/cwcf 5 Sep 2019

This work focuses on a specific classification problem, where the information about a sample is not readily available, but has to be acquired for a cost, and there is a per-sample budget.

Classification with Costly Features using Deep Reinforcement Learning

jaromiru/cwcf 20 Nov 2017

We study a classification problem where each feature can be acquired for a cost and the goal is to optimize a trade-off between the expected classification error and the feature cost.

Classification with Costly Features in Hierarchical Deep Sets

jaromiru/rcwcf 20 Nov 2019

In this work, we extend an existing deep reinforcement learning-based algorithm with hierarchical deep sets and hierarchical softmax, so that it can directly process this data.