Questions
Syllabus
Qns. By Syllabus

Semester

Subject

Year

Bachelors Level/Fourth Year/Seventh Semester/Science csit/seventh semester/data warehousing and data mining/syllabus wise questions

B.Sc Computer Science and Information Technology

Institute of Science and Technology, TU

Data Warehousing and Data Mining (CSC420)

Year Asked: 2078, syllabus wise question

Classification and Prediction
1.
Consider the following data set. Find out whether the object with attribute Confident = Yes, Sick = No will Fail or Pass using Bayesian classification.

$\begin{array}{c|c|c|c} \text{Confident} & \text{Studied} & \text{Sick} & \text{Result} \\ \hline \text{Yes} & \text{No} & \text{No} & \text{Fail} \\ \text{Yes} & \text{No} & \text{No} & \text{Pass} \\ \text{No} & \text{Yes} & \text{Yes} & \text{Fail} \\ \text{No} & \text{Yes} & \text{Yes} & \text{Pass} \\ \text{Yes} & \text{Yes} & \text{Yes} & \text{Pass} \\ \end{array}$
[5]
2.
How do you evaluate the accuracy of a classifier? Discuss the advantages of using K-fold cross validation. [5]
Cluster Analysis
1.
How do you compare two classifiers? Given the points A(3,7), B(4,6), C(5,5), D(6,4), E(7,3), F(6,2), G(7,2) and H(8,4), find the core points, border points and outliers using DBSCAN. Take Eps 2.5 and MinPts = 3. [10]
2.
Apply K(=2)-Means algorithm over the data (185, 72), (170, 56), (168, 60), (179, 68), (182, 72), (188, 77) up to two iterations and show the clusters. Initially choose first two objects as initial centroids. [5]
Data Cube Technology
1.
What are the choices for data cube materialization? Explain the strategies for cube computation. [5]
Data Preprocessing
1.
Define data discretization. Describe the tasks for data preprocessing. [5]
Graph Mining and Social Network Analysis
1.
Show the conflict between theory of balance and status. How do you improve Apriori? [5]
Introduction to Data Mining
1.
When a pattern is said to be interesting? List the issues of data mining. [5]
Introduction to Data Warehousing
1.
Write down any one advantage and disadvantage of MOLAP over ROLAP. Define signed network and how do you check whether it is balanced or not? How beam search reduces the space complexity? Illustrate with an example. [10]
2.
Differentiate between star schema and snow flake schema. List any two methods for data normalization. [5]
Mining Frequent Patterns
1.
How concept hierarchy is used in extracting information? Generate the frequent pattern from the following data set using FP growth, where minimum support=3.

$\begin{array}{|c|l|}\hline \text{T\_ID} & \text{ITEMS} \\ \hline 1 & \text{A,B,C,D,F,H} \\ 2 & \text{A,D,E,F} \\ 3 & \text{C,D,F} \\ 4 & \text{B,H} \\ 5 & \text{A,C,F,G,H} \\ 6 & \text{C,D,E,G} \\ 7 & \text{A,C,D,I} \\ \hline \end{array}$
[10]
Mining Spatial, Multimedia, Text and Web Data
1.
Define spatial data mining. What are the challenges of multimedia mining? Describe with an example. [5]