LAIM is a supervised discretization method for multi label data [1] and Python-LAIM is a implementation of LAIM. It is an adaptation of Python-CAIM.
CLI Options
usage: caim.py [-h] [-t TARGET_FIELD] [-o OUTPUT_PATH] [-H] [-q] input_file
LAIM Algorithm Command Line Tool and Library
positional arguments:
input_file CSV input data file
optional arguments:
-h, --help show this help message and exit
-t TARGET_FIELD, --target-field TARGET_FIELD
Target field as an integer (0-indexed) or string
corresponding to column name. Negative indices (e.g.
-1) are allowed.
-o OUTPUT_PATH, --output-path OUTPUT_PATH
File path to write discretized form of data in CSV
format
-H, --header Use first row as column/field names
-q, --quiet Minimal information is printed to STDOUT
Interval Output
Intervals are printed in the form:
[ 0.13 0.34 0.39 0.66]
Which should be interpretted as:
[0.13, 0.34](0.34, 0.39](0.39, 0.66]
The output dataset will use the right-end of each interval as the discretized value.
[1] Cano, A., Luna, J. M., Gibaja, E. L., & Ventura, S. (2016). LAIM discretization for multi-label data. Information Sciences, 330, 370-384.