A Universal Method for Intelligent Judgement

DOI

10.2991/caai-17.2017.73How to use a DOI?

Keywords

intelligent judgementt; model; feature vectors; machine learning; svm

Abstract

In this paper, a universal method is proposed for intelligent judgement, which relies on feature vectors representing each case to enable intelligent judgement via machine learning algorithms. The process to extract feature vectors consists of three main steps: modeling the case, building feature words lists, and extracting the vectors. After feature vectors are built, kNN and SVM algorithms are used to train the classification model, and the performance is evaluated through the experiments.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Mingzhe Li
AU  - Hongli Zhang
AU  - Lin Ye
AU  - Chuanwang Ma
PY  - 2017/06
DA  - 2017/06
TI  - A Universal Method for Intelligent Judgement
BT  - Proceedings of the 2017 2nd International Conference on Control, Automation and Artificial Intelligence (CAAI 2017)
PB  - Atlantis Press
SP  - 324
EP  - 328
SN  - 1951-6851
UR  - https://doi.org/10.2991/caai-17.2017.73
DO  - 10.2991/caai-17.2017.73
ID  - Li2017/06
ER  -