try different methods to predict 2 categories

Today, I tried different methods to predict 2 categories. But they all did not perform very well.

Summary:

Uwater and Uoil means unflushed water and unflushed oil.

I separate data into training (80%) and testing (20%) data.

1. The first is k-nearest neighbor model. The accuracy of predicting testing data is just about 60% for predicting the 2nd category (which is more complicate).

2. The second is SVM model. It can just predict 2 classes. So it cannot be applied into 2nd category prediction.

3. The third is discriminant analysis classification model. The accuracy of predicting testing data is just about 50% for predicting the 2nd category.

Next week, I will try to find ways to improve the prediction of 2 categories.