BITM Data Warehousing and Data Mining

Is KDD and Data mining same?

List any two example of categorical data.

List any two applications of data mining

Given the following dataset: 34, 41, 55, 62, 38, 69, 36, 43, 54, 63, 39, 68. Perform smoothing using bin mean. Use 3 bins.

How do you measure similarity among data? Explain with example.

What do you understand by “nonvolatile” property of data warehouse?

What do you understand by concept hierarchy?

Explain fact constellation schema with a simple example.

Explain “no materialization” of a data cube. What are its advantage and disadvantage?

What is OLTP? Differentiate between ROLAP and MOLAP.

Describe the architecture of data warehouse.

(a) Discuss the works performed by load manager, warehouse manager and query manager in a data warehouse.

(b) Write short notes on: (any two)

i. Proximity based outlier detection.

ii. K-fold Cross Validation

iii. Confusion matrix

Define frequent pattern.

What do you understand by association analysis and where can it be used in real life? How do you measure strength of association rules? Given following transaction, construct a FP-Tree.:

What do you mean by training during classification process?

How do you evaluate a classifier?

Given following dataset, compute information gain of attribute “age” using ID3.

Define lazy learners. List some limitation of k-means.

What are the two parameters of DBSCAN?

Explain DBSCAN algorithm and its working.

Is outlier always harmful?

How do you detect outlier? Explain any two approaches.