Risk Minimization Framework for Multiple Instance Learning from Positive and Unlabeled Bags

Environment

Python 3.4.5 with the following modules:

• numpy
• scipy
• scikit-learn
• chainer
• gurobipy

If you do not have Gurobi license, you can substitue cvxopt or openopt for it by rewriting

_SOLVER = 'gurobi'

to each module in MI/PU/SKC.py. Please refer to their official references for further information.

Preparation

In order to prepare datasets, run

./prepare.sh

This script will download datasets from here and make necessary changes.

Experiment

You can make experiments by puskc.py like

python puskc.py --dataset [musk1|musk2|elephant|fox|tiger] --prior [true class prior]