Challenges Of Data Mining

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Data Mining Assignment # 01
Aisha Akbar (BSCS 2011) Page 1
Q1: What are the challenges of data mining?
Challenges Of Data Mining:
1. Handling of different types of data.
2. Efficiency and scalability of data mining algorithm.
3. Usefulness, certainly, and expressiveness of data mining results.
4. Expression of various kinds of data mining requests and result.
5. Interactive mining knowledge at multiple abstraction levels.
6. Mining information from different sources of data.
7. Protection of privacy and data security.
Q2: What is the use of mined information?
Uses Of Mined Information:
Data mining is also called knowledge discovery in database. In computer science, the process of discovering knowledge and relationship in large amount of data. This field combines from statistics and artificial intelligence with database management known as data set.
Data mining is used in business (banking, insurance), government security, science research etc.
Q3: How can we classify data miners?
Classification Of Data Mining Techniques: …show more content…

DHP also reduced the size of database by not only trimming but also pruning the number of transaction in the database.
Q7: What is an interesting association rule?
An Interesting Association Rule:
All the discovered strong association rules are interesting enough to present.
Q8: How sampling can produce effective and efficient results?
Ans: The several applications required mining transaction data to capture the customer’s behavior. The efficiency of data mining is more important factor than requirement of accuracy of the result. As the size of database increase now a days very fastly, its can be an effective approach to data mining.
Q9: Describe offline and online data analysis techniques briefly?
Ans:
Q10: Define supervised and unsupervised learning in details?
Supervised And Unsupervised Learning:
 In supervised, the model defines one set of observation, called

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