Comparison of Machine Learning Algorithm's Performance Based on Decision making in Autonomous Car

被引：0

作者：

Thammachantuek, Ittikon ^{[1
]}

Kosolsomnbat, Somkiat ^{[2
]}

Ketcham, Mahasak ^{[1
]}

机构：

[1] King Mongkuts Univ Technol North Bangkok, ITMRC, Fac Informat Technol, Bangkok, Thailand

[2] Thammasat Univ, Fac Sci & Technol, Dept Data Sci & Innovat, Pathum Thani, Thailand

来源：

2018 INTERNATIONAL JOINT SYMPOSIUM ON ARTIFICIAL INTELLIGENCE AND NATURAL LANGUAGE PROCESSING (ISAI-NLP 2018) | 2018年

关键词：

Autonomous car; Machine Learning; ML; Model prediction;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper presents the performance comparison of popular supervised learning algorithms: SVM, MLP, CNN, DT, and RF. These algorithms are used for road images recognition. All images are collected by our model car. They are labeled with four different classes: left, right, forward and stop. We use 90% of them for training and use 10% for testing each model. The result shows that, CNN has the best accuracy about 83.45%.

引用

页码：114 / 119

页数：6

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