enc4ppm 0.1.8

Encode logs for predictive process monitoring

Encoding For Predictive Process Monitoring (enc4ppm)

enc4ppm is a Python package than provides common process mining encodings.

Documentation and reference.

Features

• Frequency, simple-index and complex-index encodings
• Next activity, remaining time and outcome labelings
• Save encoder to disk for later use
• Freeze encoder on training set, then use it on unseen data (automatic handling of unknown values)
• Standardize numerical features
• Convert categorical features to one-hot encoding, or keep them as strings
• Add time features (time since case start and time since last event) to the encoding

Installation

Using pip:

pip install enc4ppm

Example

The following example performs frequency encoding with latest payload for next activity prediction task:

import pandas as pd

from enc4ppm.frequency_encoder import FrequencyEncoder
from enc4ppm.constants import LabelingType

# Load log
log = pd.read_csv('bpic2012.csv')

# Create encoder
encoder = FrequencyEncoder(
    labeling_type=LabelingType.NEXT_ACTIVITY,
    include_latest_payload=True,
    attributes=['AMOUNT_REQ'],
)

# Encode log
encoded_log = encoder.encode(log)

Development

Documentation

Documentation is provided by mkdocs. To build and push the documentation website to GitHub, run the following command: mkdocs gh-deploy.

License

MIT License