---
title: "hqqqqy (@mathisimple) | Hashnode"
description: "hqqqqy (@mathisimple) writes on Hashnode. Read their latest articles and follow their work."
url: "https://hashnode.com/@mathisimple"
---

@mathisimple

# hqqqqy

@mathisimple · Joined April 2026

### [Why Naive Bayes Still Outperforms Fancy Models When Data Is Messy](https://mathisimple.hashnode.dev/why-naive-bayes-still-outperforms-fancy-models-when-data-is-messy?utm_source=hashnode&utm_medium=feed)

Learn when Naive Bayes outperforms complex models on messy, sparse, or small datasets. Real fraud detection case study with production metrics.

10 min read · [mathisimple.hashnode.dev](https://mathisimple.hashnode.dev/why-naive-bayes-still-outperforms-fancy-models-when-data-is-messy?utm_source=hashnode&utm_medium=feed)

[Apr 13](https://hashnode.com/posts/why-naive-bayes-still-outperforms-fancy-models-when-data-is-messy/69dd0091f57346bc1e0d0117)

### [Why Your PCA Pipeline Works in Notebooks But Fails in Production](https://mathisimple.hashnode.dev/how-one-scaling-bug-silently-broke-my-entire-recommendation-engine?utm_source=hashnode&utm_medium=feed)

Learn why PCA works in testing but fails in production. Complete debugging checklist + e-commerce dataset example showing variance preservation failur

8 min read · [mathisimple.hashnode.dev](https://mathisimple.hashnode.dev/how-one-scaling-bug-silently-broke-my-entire-recommendation-engine?utm_source=hashnode&utm_medium=feed)

[Apr 12](https://hashnode.com/posts/how-one-scaling-bug-silently-broke-my-entire-recommendation-engine/69dbc33faadf1107e2ff5f01)

### [The Entropy vs Gini Debate No One Tells Engineers About](https://mathisimple.hashnode.dev/the-entropy-vs-gini-debate-no-one-tells-engineers-about?utm_source=hashnode&utm_medium=feed)

Comprehensive benchmark of Gini impurity vs entropy across 47 datasets. Learn when splitting criteria choice impacts accuracy and when it's irrelevant

7 min read · [mathisimple.hashnode.dev](https://mathisimple.hashnode.dev/the-entropy-vs-gini-debate-no-one-tells-engineers-about?utm_source=hashnode&utm_medium=feed)

[Apr 10](https://hashnode.com/posts/the-entropy-vs-gini-debate-no-one-tells-engineers-about/69d91149c8e5007ddbb6e0c2)

### [Why Feature Scaling Matters: Three Cases Where the Same Data Gives Opposite Results](https://mathisimple.hashnode.dev/why-feature-scaling-matters-three-cases-where-the-same-data-gives-opposite-results?utm_source=hashnode&utm_medium=feed)

See how unscaled features distort kNN, bias PCA, and slow neural networks. Learn when to use standardization vs min-max scaling.

8 min read · [mathisimple.hashnode.dev](https://mathisimple.hashnode.dev/why-feature-scaling-matters-three-cases-where-the-same-data-gives-opposite-results?utm_source=hashnode&utm_medium=feed)

[Apr 8](https://hashnode.com/posts/why-feature-scaling-matters-three-cases-where-the-same-data-gives-opposite-results/69d67544707c1ce7684d55c5)

### [Machine Learning Data Preprocessing: The Mistakes That Break Models Before Training](https://mathisimple.hashnode.dev/machine-learning-data-preprocessing-the-mistakes-that-break-models-before-training?utm_source=hashnode&utm_medium=feed)

Learn the machine learning preprocessing pipeline: inspection, handling missing values, encoding, scaling, and splitting data the right way.

9 min read · [mathisimple.hashnode.dev](https://mathisimple.hashnode.dev/machine-learning-data-preprocessing-the-mistakes-that-break-models-before-training?utm_source=hashnode&utm_medium=feed)

[Apr 7](https://hashnode.com/posts/machine-learning-data-preprocessing-the-mistakes-that-break-models-before-training/69d5132b5da14bc70e5d7628)