Exam 10: Data Mining

The first step in creating a classification tree involves

The regression approach can be used in the two-group discriminant analysis problem because

The discriminant score is denoted by

Exhibit 10.4 The information below is used for the following questions. A manager wants to classify people as belonging to one of two groups based on two scores. The manager has collected data on four current employees and has performed a regression analysis on the data. The data for the problem and the relevant output are shown below. -Refer to Exhibit 10.4. Compute the discriminant score and predicted group for someone with Score 1 of 238 and Score 2 of 140.

The Fisher classification scores can be converted to

Affinity analysis is a data mining technique that attempts to discover

Neural networks are

A correlation coefficient

Oversampling forces a classification method to

Exhibit 10.1 The following questions are based on the problem description and the output below. A college admissions officer wants to evaluate graduate school applicants based on their GMAT scores, verbal and quantitative. Students are classified as either successful or not-successful in their graduate studies. The officer has data on 20 current students, ten of whom are doing very well (Group 1) and ten who are not (Group 2). ​ ​ ​ ​ -Refer to Exhibit 10.1. Suppose that for a given observation, the difference between Mahalanobis distances between group 1 and 2 (G1-G2) is big and positive. This means that

Exhibit 10.6 The information below is used for the following questions. An investor wants to classify companies as being either a good investment, Group 1, or a poor investment, Group 2. He has gathered Liquidity, Profitability and Activity data on 18 companies he has invested in and run a regression analysis. Discriminant Analysis output has also been generated. The data for the problem and the relevant output are shown below. ​ ​ ​ ​ ​ ​ -Refer to Exhibit 10.6. What formulas should go in cells C22:D23, E4:G24, and F24 of the spreadsheet?

Exhibit 10.4 The information below is used for the following questions. A manager wants to classify people as belonging to one of two groups based on two scores. The manager has collected data on four current employees and has performed a regression analysis on the data. The data for the problem and the relevant output are shown below. -Refer to Exhibit 10.4. What formulas should go in cells C8:D9 and E4:G10 of the spreadsheet?

In the k nearest neighbor technique, a large value of k produces classifications that

Exhibit 10.3 The information below is used for the following questions. A loan officer wants to determine if people will be late in making loan payments. She has information of 18 current loans including the applicants income, level of assets and whether or not the person has been late on payments. She has performed an analysis on the data and obtained the output shown below. ​ ​ ​ ​ ​ ​ ​ -Refer to Exhibit 10.3. What formulas should go in cells C22:D23 and E4:F24 of the spreadsheet?

Suppose that there are 3 variables in a data set. Approximately how many data records are required using a rule of thumb discussed in the textbook?

The dependent variable in the regression equation represents

The parameters of the logistic regression model

Two common ways of measuring impurity are ___________ and _____________

Suppose that a data set contains a variable EDUCATION, which has 7 discrete levels. EDUCATION is an example of

Exhibit 10.1 The following questions are based on the problem description and the output below. A college admissions officer wants to evaluate graduate school applicants based on their GMAT scores, verbal and quantitative. Students are classified as either successful or not-successful in their graduate studies. The officer has data on 20 current students, ten of whom are doing very well (Group 1) and ten who are not (Group 2). ​ ​ ​ ​ -Refer to Exhibit 10.1. What is the quantitative test score value of the group centroid for group 2?