A Universal Method for Intelligent Judgment

摘要

In this paper, a universal method is proposed for intelligent judgment, 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.