Outlines
0.Introduction to Big Data
1.chap1_intro
2.chap2_data
3.KDD+CRISP-DM
4.chap2_ DataExploration+Visualisation
5.chap3_DecisionTree
6. Overfit
7. Rule-based
8. Naive-Bayes
9. K-nearest neighbour
10. Linear Regression (chapter1, chapter2, chapter3)
11. ANN
12. Clustering Analysis
13. Cluster(Hierarchical)Example
14. Cluster(K-means)Example
15. Association(Analysis)
Weka1(DT)
Weka2(TrainandTest)
Weka3(ANN)
Weka4(Measure+Performance)
Weka5(AssocationAnalysis)
Weka6(ClusterAnalysis)
Data(regression_1)
Data(regression_2)
ANN(OR).xlsx
ANN(Con).xlsx
Cluster(k-means).xlsx
Assignment 1
Assignment 2
Assignment 3 (iris, e-commerce sales data , Movie Stars data)
Assignment4(DT)
Assignment 5 (DT+Weka)
Assignment 6 (DT+Rule+Weka)
Assignment 7 (K-nearest neighbor)
Assignment 8 (Regression)
Assignment 9 (ANN)
Assignment10(Hier-cluster)
Assignment11(K-meas)
Assignment12(Association)
Lab2(DT)
Lab3(Rule+Bayes+Knn)