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This repository contains the project where the goal is to develop a machine learning model that can accurately predict car prices based on various features. We explored multiple models including K-Nearest Neighbor, Decision Tree, Catboost Classifier, and Light Gradient Boosting Classifier.

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Prince0511/Car-Pricing-Classification

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๐Ÿš— Car Pricing Classification Project ๐Ÿ“Š

Goal: Develop a machine learning model to predict car prices based on features ๐Ÿ“ˆ

Models used:

K-Nearest Neighbor ๐Ÿงฎ Decision Tree ๐ŸŒณ Catboost Classifier ๐Ÿฑ Light Gradient Boosting Classifier ๐ŸŒŸ Classification: Categorize cars into price ranges (low, medium, high) ๐Ÿ“‰๐Ÿ“Š๐Ÿ“ˆ

Dataset: Large dataset of cars with prices and features ๐Ÿ“š

Evaluation: Metrics including accuracy, precision, recall, and F1-score โš–๏ธ

Application: Assist buyers/sellers in making informed decisions ๐Ÿ›’๐Ÿ’ฐ

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This repository contains the project where the goal is to develop a machine learning model that can accurately predict car prices based on various features. We explored multiple models including K-Nearest Neighbor, Decision Tree, Catboost Classifier, and Light Gradient Boosting Classifier.

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