本研究使用機器學習工具Orange進行九種模型的比較，先將處理好的資料

本研究使用機器學習工具Orange進行九種模型的比較，先將處理好的資料以隨機方式分為Train data和Test data進入模型訓練，模型會以Train data為基礎，去判斷Test data的屬性，再與原始Test data的屬性比較，判斷預測是否正確。

結果 (英文) 1:

In this study, using machine learning tool Orange Compare nine kinds of models, the first good information processing in a random manner into Train data and Test data into the model train, Train data model will be the basis to judge attribute Test data, and then Test data is compared with the original properties, it is determined whether the prediction is correct.

結果 (英文) 2:

This study uses the machine learning tool Orange to compare nine models, first by randomly dividing the processed data into Train data and Test data into model training, which will determine the properties of Test data based on dataTrain, and then with the original Test data. Data's properties are compared to determine whether the prediction is correct.

結果 (英文) 3:

In this study, the machine learning tool orange is used to compare nine models. Firstly, the processed data is divided into train data and test data into model training in a random way. The model will judge the attribute of test data based on train data, and then compare with the attribute ratio of original test data to determine whether the prediction is correct.