CAR PRICE PREDICTION USING RANDOM FOREST AND KNN

SOESANTO, OEI HEINRICH HANJAYA (2023) CAR PRICE PREDICTION USING RANDOM FOREST AND KNN. Other thesis, Universitas Katholik Soegijapranata Semarang.

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Abstract

Today we will be looking at a car price prediction model. Cars are usually classified into different groups according to their weight-light car, medium car and heavy weight car. The author start by collecting examples of prices for several cars. Each brand's price, model, and year are unique. Then, using orange data mining, we train a K-Nearest Neighbors (KNN) and a random forest on the training data. The results of this project will determine whether orange has good performance and which algorithm has the best results for car price datasets using K-Nearest Neighbors (KNN) or Random Forest.

Item Type: Thesis (Other)
Subjects: 000 Computer Science, Information and General Works > 004 Data processing & computer science
Divisions: Faculty of Computer Science > Department of Informatics Engineering
Depositing User: mr AM. Pudja Adjie Sudoso
Date Deposited: 04 Apr 2023 06:00
Last Modified: 18 Sep 2024 03:12
URI: http://repository.unika.ac.id/id/eprint/31393

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