BUSINESS ANALYTICS: CHAPTER 9 – PREDICTIVE DATA MINING

_____ is the process of estimating the value of a categorical outcome variable.

a. Sampling

b. Prediction

c. Classification

d. Validation

c

1. In classification, which of the following would be considered as a categorical variable for a credit approval decision for a requester?

a. marital status of the requester

b. reject or accept credit approval

c. income of the requester

gender of the requester

b

1. The effectiveness of a classification method can be judged by computing the misclassification errors and summarizing them in a

a. pivot table

b. payoff table

c. dendrogram

d. confusion matrix

d

1. Test set is the data set used to:

a. build the data mining model.

b. estimate accuracy of candidate models on unseen data.

c. estimate accuracy of final model on unseen data.

show counts of actual versus predicted class values

c. estimate accuracy of final model on unseen data.

1. An observation is classified as Class 1 if

a. the predicted probability of this observation to be in Class 1 is less than the cutoff value

b. the predicted probability of this observation to be in Class 1 is greater than or equal to the cutoff value

c. the allowable probability of making Class 1 error is less than the test p-value

d. the allowable probability of making Class 1 error is greater than or equal to the test p-value.

b. the predicted probability of this observation to be in Class 1 is greater than or equal to the cutoff value

1. In the k-nearest neighbor method, when the value of k is set to 1,

a. the classification or prediction of a new observation is based solely on the single most similar observation from the training set.

b. the new observation's class is naïvely assigned to the most common class in the training set.

c. the new observation's prediction is used to estimate the anticipated error rate on future data over the entire training set.

d. the classification or prediction of a new observation is subject to the smallest possible classification error.

a. the classification or prediction of a new observation is based solely on the single most similar observation from the training set.

1. is a generalization of linear regression for predicting an outcome of a binary variable.

a. Multiple linear regression

b. Logistic regression

c. The k-nearest neighbors' method

d. Cluster analysis

b. Logistic regression