Active learning

To install dependencies

Update Anaconda to the latest version

conda update conda

Install dependencies with Anaconda

conda env create -f environment.yml

conda activate al-env

To run

Run active learning

python3 run.py --strategy <Strategy name> --dataset <Dataset name>

e.g to run the proposed CIRAL framework on the CIFAR-10 dataset, type the following command

python3 run.py --strategy CIRAL --dataset CIFAR10

Parameters

The strategy and dataset parameter is optional and can also be specified in config.py. The different strategies and datasets are listed below. The Kaggle, AILARON and Pastore datasets needs to be separately downloaded. The Kaggle is available with the command

kaggle competitions download -c datasciencebowl

The Pastore is available at https://ibm.box.com/v/PlanktonData

Strategies

Strategy	Command
All data	ALL-DATA
BADGE	BADGE
CIRAL	CIRAL
CORESET	CORESET
DFAL	DFAL
K-MEANS	KMEANS
LEARNING LOSS	LEARNING_LOSS
MAX ENTROPY	MAX_ENTROPY
RANDOM BENCHMARK	RANDOM
SOFTMAX HYBRID	SOFTMAX_HYBRID
UNCERTAINTY	UNCERTAINTY

Datasets

Dataset	Command
CIFAR-10	CIFAR10
Kaggle	PLANKTON10
AILARON	AILARON
Pastore	PASTORE

CIRAL framework

Screen session

Screen session allows to detach terminal processes so that they continue when quitting the ssh-session.

to create a screen in linux type

screen

Detach screen

Ctrl+a d

List screens

screen -ls

Attach to screen

screen -r <Screen Name>

to rename the screen

Ctrl+a, :sessionname <Screen Name>

to kill a screen, must be attached to the screen

Ctrl+A K, y

lundha/Active-Learning

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