A Review of Machine Learning Techniques using Decision Tree and Support Vector Machine

被引：0
|
作者：
Somvanshi, Madan [1 ]
Tambade, Shital [1 ]
Chavan, Pranjali [1 ]
Shinde, S. V. [1 ]
机构：
[1] Pimpri Chinchwad Coll Engn, Dept Informat Technol, Pune, Maharashtra, India
来源：
2016 INTERNATIONAL CONFERENCE ON COMPUTING COMMUNICATION CONTROL AND AUTOMATION (ICCUBEA) | 2016年
关键词：
classification; machine learning; decision tree; id3; support vector machine; kernel;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, the brief survey of data mining classification by using the machine learning techniques is presented. The machine learning techniques like decision tree and support vector machine play the important role in all the applications of artificial intelligence. Decision tree works efficiently with discrete data and SVM is capable of building the nonlinear boundaries among the classes. Both of these techniques have their own set of strengths which makes them suitable in almost all classification tasks.
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页数：7
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