---
title: "Train Classical ML Models on Large Datasets"
url: https://daily.dev/posts/train-classical-ml-models-on-large-datasets-e0kcuegc6
source_url: https://blog.dailydoseofds.com/p/train-classical-ml-models-on-large
type: article
source: "Daily Dose of Data Science | Avi Chawla | Substack"
published: 2024-04-18T20:44:14.812Z
updated: 2024-05-09T09:03:00.647Z
tags: ["machine-learning", "big-data", "random-forest"]
reading_time: 4
upvotes: 2
comments: 0
language: en
---

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# Train Classical ML Models on Large Datasets

**[Daily Dose of Data Science \| Avi Chawla \| Substack](https://daily.dev/sources/dailydoseofds)** · 4 min read · 2 upvotes · 0 comments

## Summary

Learn how to train classical ML models on large datasets using the random patches approach, which has been shown to perform better than traditional random forest. This approach involves sampling random data patches and training a tree model on them.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://blog.dailydoseofds.com/p/train-classical-ml-models-on-large>

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---

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

[View this post on daily.dev](https://daily.dev/posts/train-classical-ml-models-on-large-datasets-e0kcuegc6)