Instance selection of linear complexity for big data

Machine Learning algorithms for MOA designed to cope with concept drift.

Instance Selection for Big Data

A new fast instance selection method for machine learning.

Instance Selection using numpy and pyspark

Local set computation for multi-label data sets

Instance selection for multi-label data by means of data transformation methods: binary-relevance, label powerset and random k-labelsets

Simply and consistently present a handful of instance types.

Fast instance selection method

Border Instances Reduction using Classes Handily (BIRCH)

Instance selection algorithms based on DROP for regression

Instance selection algorithms based on discretization for regression

Graph Reduction for Instance SelecTion - A comprehensive toolkit for evaluating 30+ graph reduction techniques.

Instance Selection and Prototype Selection investigation with metaheuristics

Graph Attention-based Instance Selection (GAIS). Python package for a novel instance selection method utilizing graph attention networks.

Unsupervised instance selection via conjectural hyperrectangles