Page 61 - DCAP603_DATAWARE_HOUSING_AND_DATAMINING

Unit 3: Data Mining Techniques

State whether the following statements are true or false: notes
8. Data are known to be crude information and not knowledge by themselves.

9. Neural Networks is not a type of Data Mining techniques.
10. A variety of pieces of information are usually known about an applicant for a loan.
11. Genetic algorithms require certain data structure.

3.11 review Questions

1. Write a short note on regression and correlation.
2. Define similarity. List the commonly used similarity measures.

3. What is meant by distance or dissimilarity measures? Elaborate.
4. Define a decision tree and a decision tree model.
5. Present and discuss a prediction technique using decision trees.
6. Write short notes on the following terms:

(a) Neural network
(b) Neural network model
(c) Artificial neural network
(d) Activation function
7. What is an activation function? Explain the different types of activation functions.

8. Write a short note on genetic algorithms.
9. Define a genetic algorithm. Present and explain a genetic algorithm.
10. Discuss the merits and demerits of genetic algorithms.
11. What do you mean by genetic algorithms?
12. Describe statistical perspective on data mining.

13. What do you mean by statistics and why it’s so important?
14. Explain similarity measures in detail.
15. Describe various applications of genetic algorithms in data mining.

answers: self assessment

1. Statistics 2. Data
3. Similarity measures 4. information retrieval (IR)

5. Overlap coefficient 6. Neural networks
7. Genetic algorithms 8. True
9. False 10. True
11. True

LoveLy professionaL university 55