IS328 Data Mining
Data Mining with WEKA Explorer
Week 5: Lab Exercises
Tasks
1) Download the LabOne -RawData and perform the tasks outlined there in.
2. Run Wekas J48 classifier on the initial data with the test option set to 66%
so that 66% of the data i

Discovering Association Rules
CS328 Data Mining
Lecture 7-2
Overview
Association Rule Problem
Applications
The Apriori Algorithm
Discovering Association Rules
Techniques to Improve Efficiency of
Association Rule Mining
Measures for Association Rules

Density-Based
Clustering
CS328 Data Mining
Week 10
UIC - CS 594
1
Assignment 2 - Overview
Due: October 17, Monday 11:55 pm
PART A Association Rule Mining
Manual and Weka Based Exercises
PART
Manual and Weka Based Exercises
PART
B Partitional Clustering

Artificial
Neural Networks
IS328 Data Mining
Week 11-2
Overview
Basics
of Neural Network
Advanced
Features of Neural Network
Applications
Summary
I-II
Basics of Neural Network
What is a Neural Network
Neural Network Classifier
Data Normalization
N

Q1. Dimensionality reduction reduces the data set size by removing _.
A. relevant attributes.
B. irrelevant attributes.
C. derived attributes.
D. composite attributes.
ANSWER: B
Q2
Consider discretizing a continuous attribute whose values are listed below

K-Medoids Clustering Example
Cluster the following data set of ten objects into two clusters i.e. k = 2.
Consider a data set of ten objects as follows:
Distribution of the data
X1
X2
X3
X4
X5
X6
X7
X8
X9
X10
2
3
3
4
6
6
7
7
8
7
6
4
8
7
2
4
3
4
5
6
Step 1

Mining sequence patterns in
transactional databases
IS328 Data Mining
Week 11
Week 11 Announcements
Assignment 2 is now on Moodle.
It is due on October 17, Monday at 5 pm.
Dr Kerese Manueli will begin his lectures from
Week 12.
2
Week 11 Announcements

Page 1 of 8
Assignment 1 - Performing Data Mining tasks using WEKA
IS328 Data Mining
Semester 2, 2016
Weight: 20%
Due Date: Monday, 5th September, 2016; 11:55 pm
Working Group:
You may work individually or in pairs
In this assignment you will experiment w

Semester 2, 2016
IS328 Data Mining
Tutorial Week 9
Frequent Itemsets and
Association Rule Mining
Problem 1- Appropriate Algorithm
(a)
Explain the difference between the following:
(i)
Frequent Itemset
(ii)
Candidate Itemset
One Mark Each
A frequent items

Lab Exercise One
Data Preprocessing with WEKA Explorer
Preview of the raw data
1. Open a terminal window from the left bar. Go to directory /opt/weak-3-6-13, then type
command :
java jar weka.jar.
2. When you get the GUI Chooser panel. Select Explorer fro