Mixuture of Probabilistic Partial Canonical Correlation Analysis

Code for our paper Causal Patterns: Extraction of Multiple Causal Relationships by Mixture of Probabilistic Partial Canonical Correlation Analysis.

Publication

Hiroki Mori, Keisuke Kawano and Hiroki Yokoyama. "Causal Patterns: Extraction of Multiple Causal Relationships by Mixture of Probabilistic Partial Canonical Correlation Analysis" Proceedings of the 2017 IEEE International Conference on Data Science and Advanced Analytics. pp.744-754 https://arxiv.org/abs/1712.04221

Dependencies

• for mppcca.py
  • Python == 3.6
  • numpy== 1.13.1
  • scipy == 0.19.1
• for the sample programs in example directory, some additional libraries are required.
  • matplotlib
  • seaborn
  • scikit-learn

Setup

$ git clone https://github.com/kskkwn/mppcca.git
$ cd mppcca
$ conda env create --file env.yaml # if you use anaconda else install above dependencies manually.
$ source activate mppcca

Examples

$ python example/toy_scatter_data/toy_scatter_data.py 
$ python example/time_series_exp/time_series_exp.py

"Extraction of Multiple Causal Relationships" from your own data

$ python mppcca_from_csv.py -i example/data.csv -k 3 -d 1 -e 1 -o temp.csv
$ python mppcca_from_csv.py -i ${input_file} -k ${nb_clusters} -d ${delay_time} -e ${embedding_time} -o ${output_file}