author: Tzu-Ching Wu(George)

This project contains the source code of Kaggle_Customer GUI, a matlab-based GUI for the data preprocessing, feature selection, and classification method testing of the Kaggle competition: Santander Customer Satisfaction. You will obtain the averaged AUC value to evaluate classification performance after running, and can easily create the test dataset result csv file for submitting.

Two matlab-GUI related code: Customer_GUI.m and Customer_GUI.fig are provided. The subfolder /pre_data shoud contains three matlab data file: train.mat, test.mat, and ID.mat which are training dataset, testing dataset, and testing ID from Santander Customer Satisfaction website. Of course, you should have matlab installed in your compyter.

To run Kaggle_Customer-GUI, just type Customer_GUI in matlab command line.

1.Pre-data method:

• Raw data
• Normalization
• Binary

2.Feature selection

• All features
• Choice feature, and input feature numbers

3.Cross-Validation N, input integer number bigger than 2

4.Classification method

• NaiveBayes
• Decision Tree
• Discriminant classification
• K-nearest neighbor(KNN)
• Suppoer vector mechine(SVM)
• Classification Ensemble
• Backpropagation Neural Network(BPN)
• Radial basis network(RBN)
• Adaptive neuro-fuzzy inference system(ANFIS)

v1.1

• Add 4 methods including Classification Ensemble, Backpropagation Neural Network(BPN) Radial basis network(RBN), and Adaptive neuro-fuzzy inference system(ANFIS)
• Show accuracy rate of classification