`HMIL`_is univeriate time series imputation method based on Heuristic search and machine learning.
- Genetic algorithm to find optimum dependent variables
- Support Vector Machine for regression and prediction
Edit data file location and evolutationary parameter in hmli.ini:
Default parameter values:
- number of prediction observations: 12
- number of genes per chromosome: 6
- number of chromosomes per population: 10
- number of populations: 100
- cutoff rate of bad chromosome: 0.5
- cutoff correlation coefficient: 0.97
- random seed list: [1, 2, 3]
- missing rate list: [0.1, 0.4, 0.7]
- hdf5 data file: data/mei.h5
- result file: output/finalRes1.pickle
Execute the main file:
..code-block:: bash
$python main.py
It will execute parallel process and consume CPU resource a lot.
Sample data is OECD MEI monthly series. The total number series in the file is 5,411.