Labeling data using the Compose library

Compose is an open source Python library developed to generate the labels for supervised machine learning. Compose creates labels from historical data using LabelMaker.

Subject matter experts or end users write labeling functions for the outcome of interest. For example, if the outcome of interest is the amount spent by customers in the last five days, then the labeling function returns the amount spent by taking the last five days of transaction data as input. We will take a look at this example as follows.

Let us first install the composeml Python package. It is an open source Python library for prediction engineering:

pip install composeml

We will create the label for the total purchase spend amount in the next five days based on the customer’s transactions data history.

For this, let us first import composeml:

import composeml as cp

Then, load the sample data:

from demo.next_purchase import load_sample
df = load_sample...