IFM.py Package | IFM Lab

IFM.py

Information Fusion and Mining in Python

Simple and efficient tools for information fusion
Abundant multi-source data mining algorithms
Accessible to everybody, and reusable in various contexts
Built on scikit-learn, NumPy, SciPy, and matplotlib
Open source, commercially usable

If you use IFM.py, please cite us.

Machine Learning

Basic machine learning algorithms

Data processing, feature selection, dimension reduction
Classification, regression algorithms
Clustering algorithms, evaluation metrics ...
Examples

Network Measures, Operations

Basic measures and operations for networks

Size, diameter, density of networks
Degree, centrality of nodes
Closeness, transitivity of user-pair based links ...
Examples

Network Alignment

Aligning networks via shared information entities

Supervised network alignment
Semi-supervised network alignment
Unsupervised network alignment ...
Examples

Network Structure Prediction

Inferring potential structure of networks

Traditional single-network structure prediction
Inter-network structure prediction
Collective cold start structure prediction ...
Examples

Network Community Detection

Detecting communities formed in networks

Traditional single-network community detection
Mutual community detection
Cold start community detection ...
Examples

Information Diffusion

Information propagation models for networks

Traditional single-network information diffusion
Cross-network information diffusion
Random-walk based information diffusion model ...
Examples

Viral Marketing

Viral marketing in networks

Traditional single-network viral marketing strategies
Inter-network viral marketing
Tipping user identification ...
Examples

Network Embedding

Network structure to vectors

Traditional single homogeneous network embedding
Heterogeneous network embedding
Multiple aligned heterogeneous networks embedding ...
Examples