---
title: "DIY #22 - Build a Churn Detection Model from Scratch"
url: https://daily.dev/posts/diy-22---build-a-churn-detection-model-from-scratch-lsntlkfqx
source_url: https://mlpills.substack.com/p/diy-22-build-a-churn-detection-model
type: article
source: "Machine Learning Pills"
published: 2026-05-31T14:06:45.937Z
updated: 2026-05-31T14:07:14.005Z
tags: ["machine-learning", "python", "scikit", "random-forest"]
reading_time: 18
upvotes: 0
comments: 0
language: en
---

> ## Documentation Index
> Fetch the complete documentation index at: https://daily.dev/llms.txt
> Use this file to discover all available pages before exploring further.

# DIY #22 - Build a Churn Detection Model from Scratch

**[Machine Learning Pills](https://daily.dev/sources/mlpills)** · 18 min read · 0 upvotes · 0 comments

## Summary

A hands-on walkthrough for building a telecom customer churn detection model using Python and scikit-learn. Covers the full pipeline: generating a synthetic dataset with 3,333 customers and 14.3% churn rate, exploratory data analysis revealing that support call volume and international plan holders are the strongest churn signals, preprocessing with stratified splits and standard scaling, training a Random Forest classifier with class_weight='balanced' to handle imbalance, and evaluating with ROC-AUC (0.798). Explains threshold tuning via Youden's J statistic, showing that lowering the decision boundary from 0.5 to 0.376 raises recall from 48% to 67.4%. Also covers feature importance analysis and scoring new customers with risk tiers. Closes with expert notes on SHAP values, LightGBM/XGBoost as stronger alternatives, and uplift modeling as the next frontier.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://mlpills.substack.com/p/diy-22-build-a-churn-detection-model>

## Similar posts on daily.dev

- [Clustering and Classifying Customer Transaction Behavior with Machine Learning](https://daily.dev/posts/clustering-and-classifying-customer-transaction-behavior-with-machine-learning-cnkjrl1g3) · Medium · 0 upvotes · 0 comments
- [How to Improve Customer Retention in FinTech](https://daily.dev/posts/how-to-improve-customer-retention-in-fintech-yb7zsusfg) · Towards Data Science · 0 upvotes · 1 comments
- [Your Churn Threshold Is a Pricing Decision](https://daily.dev/posts/your-churn-threshold-is-a-pricing-decision-l0z7ftepq) · Towards Data Science · 0 upvotes · 0 comments

---

Tags: [#machine-learning](https://daily.dev/tags/machine-learning), [#python](https://daily.dev/tags/python), [#scikit](https://daily.dev/tags/scikit), [#random-forest](https://daily.dev/tags/random-forest)

[View this post on daily.dev](https://daily.dev/posts/diy-22---build-a-churn-detection-model-from-scratch-lsntlkfqx)