Exam 10: Data Mining

The concept behind neural networks is to

The k-nearest neighbor classification technique

In preparation for mining an analyst should

Exhibit 10.1 The following questions are based on the problem description,regression results,and the Analytic Solver Platform Discriminant Analysis report 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). Unpooled Estimates of within-group Covariance matrices are used,assuming they are different. Group Centroids Group Quantitative Verbal 1 683.8 654.2 2 610.7 605.7 $\text { Classitication Matrix }$ Actual / Predicted Group1 Group2 Total \% correct Group1 9 1 1 90.00\% 0 Group2 2 8 1 80.00\% 0 Total 1 9 2 85.00\% 1 0 -Refer to Exhibit 10.1.What is the verbal test score value of the group centroid for group 1?

A provides a visual summary of the improvements that a data mining project provides on a binary classification problem compared to a random guess

Techniques)used in prediction step of data mining include

A algorithm is used during the training process to adjust weights in a neural network

Exhibit 10.2 The following questions are based on the problem description,spreadsheet,and the Analytic Solver Platform Discriminant Analysis report 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 Group 1),marginally successful Group 2)or not- successful Group 3)in their graduate studies.The officer has data on 20 current students,7 successful Group 1),6 marginally successful Group 2)and 7 not successful Group 3). Discriminant Analysis Report October 1,2013 4:22:38 PM Unpooled Estimates of within-group Covariance matrices are used,assuming they are different. Group Centroids Group Quantitative Verbal 1 697.7142857 650.4285714 2 647.8571429 630.7142857 3 5876666667 6051666667 $\text {Group}$ $\text {Frenuencies}$ Group Relative Frequency 1 35.00\% 2 35.00\% 3 30.00\% Training Sample Classification Mahalanobis Distances $\text {Classification}$ $\text {Matrix}$ Actual / Predicted Group1 Group2 Group3 Total \% correct Group1 6 1 0 7 85.71\% Group2 0 7 0 7 100.00\% Group3 0 0 6 6 100.00\% Total 6 8 6 2 95.00\% -Refer to Exhibit 10.2.Based on the analysis presented in the spreadsheet,what percentage of the observations were correctly classified?

In using neural networks,an analyst must decide and _

Neural networks classification methodology

An Excel add-in tool used for data mining is called

Suppose that two variables are found to be significantly correlated.A researcher may

Before effectively applying the k nearest neighbor classification technique,the variables need to be

Two common ways of measuring impurity are and _

Exhibit 10.1 The following questions are based on the problem description,regression results,and the Analytic Solver Platform Discriminant Analysis report 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). Unpooled Estimates of within-group Covariance matrices are used,assuming they are different. Group Centroids Group Quantitative Verbal 1 683.8 654.2 2 610.7 605.7 $\text { Classitication Matrix }$ Actual / Predicted Group1 Group2 Total \% correct Group1 9 1 1 90.00\% 0 Group2 2 8 1 80.00\% 0 Total 1 9 2 85.00\% 1 0 -Refer to Exhibit 10.1.What number of observations is classified incorrectly?

Oversampling forces a classification method to

Exhibit 10.1 The following questions are based on the problem description,regression results,and the Analytic Solver Platform Discriminant Analysis report 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). Unpooled Estimates of within-group Covariance matrices are used,assuming they are different. Group Centroids Group Quantitative Verbal 1 683.8 654.2 2 610.7 605.7 $\text { Classitication Matrix }$ Actual / Predicted Group1 Group2 Total \% correct Group1 9 1 1 90.00\% 0 Group2 2 8 1 80.00\% 0 Total 1 9 2 85.00\% 1 0 -Refer to Exhibit 10.1.What is the straight line distance between 6,4)and 2,9)?

Logistic regression is a classification technique that

Exhibit 10.2 The following questions are based on the problem description,spreadsheet,and the Analytic Solver Platform Discriminant Analysis report 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 Group 1),marginally successful Group 2)or not- successful Group 3)in their graduate studies.The officer has data on 20 current students,7 successful Group 1),6 marginally successful Group 2)and 7 not successful Group 3). Discriminant Analysis Report October 1,2013 4:22:38 PM Unpooled Estimates of within-group Covariance matrices are used,assuming they are different. Group Centroids Group Quantitative Verbal 1 697.7142857 650.4285714 2 647.8571429 630.7142857 3 5876666667 6051666667 $\text {Group}$ $\text {Frenuencies}$ Group Relative Frequency 1 35.00\% 2 35.00\% 3 30.00\% Training Sample Classification Mahalanobis Distances $\text {Classification}$ $\text {Matrix}$ Actual / Predicted Group1 Group2 Group3 Total \% correct Group1 6 1 0 7 85.71\% Group2 0 7 0 7 100.00\% Group3 0 0 6 6 100.00\% Total 6 8 6 2 95.00\% -Refer to Exhibit 10.2.What is the verbal test score value of the group centroid for group 3?

In hierarchical clustering,the measure of similarity between clusters is/are