เนื้อหาโครงสร้างหลักสูตร

1. Model builder & Prediction for New dataset.
1.1 Unsupervised
Kmeans Clustering
1.2 Supervised (Classify algorithm)
Decision Trees
Support Vector Machines
Neural Networks
Logistic Regression

2.Basic Evaluation
Confusion Matrix

3.Graphical Performance Measures
Lift Charts
ROC Curves

Cost Curves

4.Weka experimenter training.

4.1 Standard Experiments

Simple

Advanced

4.2 Analysing Results

Setup

Saving the Results

Changing the Baseline Scheme

Statistical Significance

Summary Test

Ranking Test

4.3 Introduce Processing several PC / Machine.