This project contains code for paper Ksenia Konyushkova, Raphael Sznitman, Pascal Fua 'Learning Active Learning from Data', NIPS 2017
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Classes First push of code Nov 3, 2017
data First push of code Nov 3, 2017
exp/.ipynb_checkpoints First push of code Nov 3, 2017
lal datasets First push of code Nov 3, 2017
AL experiments.ipynb First push of code Nov 3, 2017
README.md readme file Nov 2, 2017

README.md

LAL

Code for paper Ksenia Konyushkova, Raphael Sznitman, Pascal Fua 'Learning Active Learning from Data', NIPS 2017

This code can be run with Jupyter notebook 'AL experiments'. You will need the following packages: numpy, sklearn, matplotlib, scipy, time, scipy, math, pickle. 'AL experiment' guides you through the nain steps. It uses classed from folder./Classes, data for experiments is stored in ./data, data for learning a strategy is stored in ./lal datasets and the results are written into ./exp. Class ActiveLearner implements methods Random, Uncertainty Sampling and LAL. For more details refer to the paper and comments in the code.