Exam 10: Introduction to Data Mining

The data mining approach called involves the developing of analytic models to describe the relationship between metrics that drive business performance like profitability, customer satisfaction, or employee satisfaction.

is the ratio of the number of transactions that include all items in the consequent as well as the antecedent to the number of transactions that include all items in the antecedent.

is a collection of techniques that seek to group or segment a collection of objects or observations into subsets, such that those within each subset are more closely related to one another than objects assigned to different subsets.

Which of the following is true of a training data set?

In association analysis, the antecedent and consequent are sets of items that do not have any items in common.

Which of the following would be considered a lagging measure in a restaurant using the cause-and-modeling method of data mining?

Which of the following types of data-mining methods provides probabilistic if-then statements?

In the cause-and-effect modeling, internal metrics, such as employee satisfaction, productivity, and turnover are considered to be measures.

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

Which of the following is a definition of distance between two clusters in a complete linkage clustering?

Spam filtering for e-mails can be seen as an example of which of the following types of approaches of data mining?

Which of the following is included in the data mining approach of data exploration and reduction?

If the Euclidean distance were to be represented in a right triangle, which of the following would be considered the distance between two objects of a cluster?

Exemplify the k-Nearest Neighbor algorithm of classification.

Briefly explain classification as a data-mining tool with an example.

If bs are weights, Xs are input values, and c is a constant or intercept, provide the equation for discriminant functions, L.

In the method, the distance between groups is defined as the distance between the closest pair of objects, where only pairs consisting of one object from each group are considered.

Explain how data-mining using lagging and leading measures of the cause-and-effect model can help managers make business decisions.

Divisive clustering method is different from agglomerative clustering methods in that divisive clustering methods .

Which of the following is the first stage of joining clusters in agglomerative hierarchical clustering?