Churn rate is a marketing metric that describes the number of customers who leave a business over a specific time period. . Every user is assigned a prediction value that estimates their state of churn at any given time. This value is based on:
Browsing behavior Historical purchase data among other information It factors in our unique and proprietary predictions of how long a user will remain a customer. This score is updated every day for all users who have a minimum of one conversion. The values assigned are between 1 and 5.
Your task is to predict the churn score for a website based on the features provided in the dataset.
The dataset folder contains the following files:
train.csv: 36992 x 25
test.csv: 19919 x 24
sample_submission.csv: 5 x 2
score = 100 x metrics.f1_score(actual, predicted, average="macro")