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Multiple Answer Question: What are the characteristics of the interesting patterns or knowledge data mining tends to extract from the huge amount of data? Choose

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Multiple Answer Question: What are the characteristics of the interesting patterns or knowledge data mining tends to extract from the huge amount of data? Choose all the answers that apply. previously unknown non-trivial potentially useful explicit implicit What type of variable is "letter grade of a course (e.g., A,A,B+,B, )" Ordinal variable Continuous variable Nominal variable Dichotomous variable What type of variable is "temperature"? Continuous variable Dichotomous variable Ordinal variable Nominal variable What type of variable is "frequency (e.g., always, often, sometimes, never)"? Dichotomous variable Nominal variable Continuous variable Ordinal variable For the following dataset of integer numbers "1, 1, 2, 2, 2, 3, 3, 3, 3, 3, 4, 4, 4, 5, 5, 5, 5" What is the mean, median, mode, respectively? 4, 3, 5 3.23,3,3 3.23,3,4 3.23,4,3 Multiple Answer Question: What types of errors should be cleaned in the data cleaning step? Choose all the answers that apply Missing values Value entered that does not exist for the variable (e.g., 3 entered for gender (1= male, 2= female)) Inconsistent values (e.g., Age="42" Birthday="03/07/1997") Outliers Negative numbers Given the table of transactions below: For the rule A,C=>D, what is the support? what is the confidence? support =40%, confidence =66.7% support =60%, confidence =40% support =40%, confidence =60% support =80%, confidence =40% support =60%, confidence =66.7% Multiple Answer Question: Given the table of transactions in Question 7. If the minimum support =50%, minimum confidence =50%, which of the following association rules will be identified? Choose all that applies: A==> D==>B D==>C C==>A A==> Multiple Answer Question: Given the table of transactions in Question 7. If the minimum support =50%, minimum confidence =50%, which of the following association rules will be identified? Choose all that applies: A==> D==>B D==>C C==>A A==> Given the linear regression model: University GPA =(0.675)( High School GPA )+1.097 If a student has a high school GPA 3.45, what would his University GPA be based on this model: 3.32 3.43 3.52 3.22

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