Selector

Selector selects diverse subsets from datasets using various algorithms and metrics for quantifying subset diversity.

Key Features:

• Subset Sampling Algorithms: Implements algorithms based on sample distance, similarity, and spatial partitioning.
• Diversity Metrics: Provides metrics to quantify subset diversity.
• Python Library Integration: Integrates with Scikit-Learn and other popular Python libraries.

Scientific Applications:

• Computational Chemistry: Applied in computational chemistry workflows for diverse subset selection.
• Drug Discovery: Supports drug discovery through selection of diverse compound subsets.
• Chemical Library Design: Enables diverse subset selection for chemical library design.

Methodology:

Algorithms based on sample distance, similarity, and spatial partitioning.