---
title: "Discussion on \"Building a Near-Perfect Claims Classifier: Random Forest vs XGBoost on TikTok Data (Google Advanced DA Course 5)\" | Hashnode"
description: "Discussion on \"Building a Near-Perfect Claims Classifier: Random Forest vs XGBoost on TikTok Data (Google Advanced DA Course 5)\". How I built a 99.7% accurate Random Forest model to classify TikTok claims vs opinions using Python, GridSearchCV, and NLP features."
url: "https://hashnode.com/posts/building-a-near-perfect-claims-classifier-random-forest-vs-xgboost-on-tiktok-data-google-advanced-da-course-5/6a173136badcd8afcb157c2f"
---

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# [Building a Near-Perfect Claims Classifier: Random Forest vs XGBoost on TikTok Data (Google Advanced DA Course 5)](https://danieljasme.hashnode.dev/building-a-near-perfect-claims-classifier-random-forest-vs-xgboost-on-tiktok-data-google-advanced-da-course-5?utm_source=hashnode&utm_medium=feed)

How I built a 99.7% accurate Random Forest model to classify TikTok claims vs opinions using Python, GridSearchCV, and NLP features.

May 27 · 9 min read · danieljasme.hashnode.dev  
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-   [#machine-learning](https://hashnode.com/tag/machine-learning)
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@danieljasme · Kuala Lumpur, Malaysia

  
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