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Data warehouse and Data mining: Introduction to Data Mining, Data Exploration and Preprocessing
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Data warehouse and Data mining: Introduction to Data Mining, Data Exploration and Preprocessing
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25 Questions

1. The number that occurs most often within a set of data called as ______
2. ______ partitions the objects into different groups.
3. Data mining turns a large collection of data into _____
4. _____ is the science of searching for documents or information in documents.
5. Data mining refers to ______
6. The values of a _____ attribute are symbols or names of things.
7. What kinds of data can be mined?
8. The mean is the ________ of a dataset.
9. In KDD Process, data are transformed and consolidated into appropriate forms for mining by performing summary or aggregation operations is called as _____
10. In _____, the attribute data are scaled so as to fall within a smaller range, such as -1.0 to 1.0, or 0.0 to 1.0.
11. In KDD Process, where data relevant to the analysis task are retrieved from the database means _____
12. _______ is a top-down splitting technique based on a specified number of bins.
13. Which are not related to Ratio Attributes?
14. .
15. An _____ is a data field, representing a characteristic or feature of a data object.
16. Which are not the part of the KDD process from the following
17. The data mining process should be highly ______
18. Multiple data sources may be combined is called as _____
19. Data selection is _____
20. Data often contain _____
21. In real world multidimensional view of data mining, The major dimensions are data, knowledge, technologies, and _____
22. ______ investigates how computers can learn (or improve their performance) based on data.
23. An attribute is a ____
24. _______ is the output of KDD Process.
25. _____ studies the collection, analysis, interpretation or explanation, and presentation of data.

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