Classification with Costly Features

3 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.

Datasets


Greatest papers with code

Classification with Costly Features as a Sequential Decision-Making Problem

jaara/classification-with-costly-features 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 Classification with Costly Features +2

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 Classification with Costly Features +3

Cost-Efficient Hierarchical Knowledge Extraction with Deep Reinforcement Learning

jaromiru/rcwcf 20 Nov 2019

Instead, the samples can only be represented as trees of features, with a variable and possibly unlimited depth and breadth, similar to a JSON file.

Classification Classification with Costly Features +4