CSC410 Data Warehousing and Data Mining

Data Warehousing and Data Mining: most repeated questions

Questions that have come up in more than one paper, matched by what they ask rather than exact wording. Most repeated first.

2×Asked in 2081, 2078
Distinguish between data characterization and data discrimination. What are the challenges of multimedia mining?Answer coming5
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- Distinguish between data characterization and data discrimination. What are the challenges of multimedia mining?TU Board 2081
- Define spatial data mining. What are the challenged of multimedia mining? Describe with an example.TU Board 2078
2×Asked in 2080, Model question
Explain the OLAP operations with examples.Answer coming5
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- Explain the OLAP operations with examples.TU Board 2080
- Describe any five types of OLAP operations.Model question
2×Asked in 2080, 2079
State Apriori property. Find frequent item sets and association rules from the transaction database given below using Apriori algorithm. Assume min. support is 50% and min confidence is 75%. Transaction ID Items Purchased 1 Bread, Cheese, Egg, Juice 2 Bread,…Answer coming10
See the wording in each paper
- State Apriori property. Find frequent item sets and association rules from the transaction database given below using Apriori algorithm. Assume min. support is 50% and min confidence is 75%.…TU Board 2080
- Discuss any two drawbacks of Apriori algorithm. Find frequent item sets and association rules from the transaction database given below using FP growth algorithm. Assume minimum support is 50% and…TU Board 2079
2×Asked in 2079, Model question
Discuss the concept of K means++ and Mini batch K means algorithm.Answer coming5
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- Discuss the concept of K means++ and Mini batch K means algorithm.TU Board 2079
- What is the concept mini batch k means? How DBSCAN works?Model question
2×Asked in 2082, 2078
Given the following distance matrix, find the core points and outliers using DBSCAN. Take Eps = 2.5 and MinPts = 3. Data Points A B C D E F G H A 0 1.41 2.83 4.24 5.66 5.83 6.40 5.83 B 0 1.41 2.82 4.24 4.47 5.00 4.47 C 0 1.41 2.82 3.16 3.60 3.16 D 0 1.41…Answer coming5
See the wording in each paper
- Given the following distance matrix, find the core points and outliers using DBSCAN. Take Eps = 2.5 and MinPts = 3. Data Points A B C D E F G H A 0 1.41 2.83 4.24 5.66 5.83 6.40 5.83 B 0 1.41 2.82…TU Board 2082
- 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…TU Board 2078