Custom algorithm template

You can use the following custom algorithm template to help get you started with adding a custom algorithm to MLTK.

BaseAlgo class

From base import BaseAlgo.

class CustomAlgoTemplate(BaseAlgo):
    def __init__(self, options):
        # Option checking & initializations here
        pass

    def fit(self, df, options):
        # Fit an estimator to df, a pandas DataFrame of the search results
        pass

    def partial_fit(self, df, options):
        # Incrementally fit a model
        pass

    def apply(self, df, options):
        # Apply a saved model
        # Modify df, a pandas DataFrame of the search results
        return df

    @staticmethod
    def register_codecs():
        # Add codecs to the codec manager
        pass

Using the Basealgo template in a search, reflects the input data back to the search as shown in the following example.

| fit CustomAlgoTemplate *

These are all described in detail in the $SPLUNK_HOME/etc/apps/Splunk_ML_Toolkit/bin/base.py BaseAlgo class as shown below.