# Data Warehousing Mining Questions & Answers: part2

Software Programming : Data Warehousing Mining QUESTIONS AND ANSWERS :: part2 : 1 to 5

Following Software Programming language Entrance Multiple choice objective type questions and answers will help you in Software Programming 2024 examinations :

 1.Multiple Regression means Data are modeled using a straight line Data are modeled using a curve line Extension of linear regression involving only one predicator value Extension of linear regression involving more than one predicator value All (opt1), (opt2), (opt3) and (opt4) above. ANSWER : 4 Extension of linear regression involving more than one predicator value Explanation : : Multiple Regression means extension of linear regression involving more than one predicator value.
 2.Which of following form the set of data created to support a specific short lived business situation? Personal data marts Application models Downstream systems Disposable data marts Data mining models. ANSWER : Disposable data marts Explanation : :Disposable Data Marts is the form the set of data created to support a specific short lived business situation.
 3.Concept description is the basic form of the #17. Concept description is the basic form of the Predictive data mining Descriptive data mining Data warehouse Relational data base Proactive data mining. ANSWER : 2 Descriptive data mining Explanation : :Concept description is the basis form of the descriptive data mining.
 4.Which of the following should not be considered for each dimension attribute? Attribute name Rapid changing dimension policy Attribute definition Sample data Cardinality. ANSWER : Rapid changing dimension policy Explanation : : Rapid changing dimension policy should not be considered for each dimension attribute.
 5.The apriori property means If a set cannot pass a test, all of its supersets will fail the same test as well To improve the efficiency the level-wise generation of frequent item sets If a set can pass a test, all of its supersets will fail the same test as well To decrease the efficiency the level-wise generation of frequent item sets All (opt1), (opt2), (opt3) and (opt4) above. ANSWER : 2 To improve the efficiency the level-wise generation of frequent item sets Explanation : : The apriori property means to improve the efficiency the level-wise generation of frequent item sets.

More Data Warehousing Mining QUESTIONS AND ANSWERS available in next pages

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