Question 1

Which of the following uses the sum of squares between the objects in the cluster when measuring their distances?

Accepted Answer

Ward's hierarchical clustering uses the sum of squares between the objects in the cluster to measure distances, aiming to minimize the total within-cluster variance.

Question 2

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

Accepted Answer

Complete linkage clustering defines the distance between two clusters as the distance between the most distant pair of objects, one from each group. This method ensures that all elements in each cluster are within a maximum distance from each other.

Question 3

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

Accepted Answer

In agglomerative hierarchical clustering, the first stage involves joining the two clusters that are closest to each other, typically measured by some form of distance like Euclidean distance. This process starts with each data point as its own cluster and iteratively merges the closest pairs of clusters until all points are merged into a single cluster or a stopping criterion is met.

Question 4

In a k-Nearest Neighbors algorithm, similarity of records is based on the .

Accepted Answer

The k-Nearest Neighbors algorithm determines similarity based on the closeness of a record to numerical predictors in other records, typically using distance metrics like Euclidean distance.

Question 5

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

Accepted Answer

Spam filtering for e-mails is a classification problem in data mining, where emails are classified into "spam" or "not spam" based on their content, sender, and other attributes.

Question 6

Which of the following features of classification, used in Excel, for a particular database will necessarily be coded to a certain value?

Accepted Answer

The answer of Which of the following features of classification,...

Question 7

Which of the following is true of cluster analysis?

Accepted Answer

Cluster analysis is a type of unsupervised learning that groups objects based on their similarities, but it does not provide a definitive answer or prediction. Instead, it reveals the natural groupings or patterns within the data.

Question 8

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.

Accepted Answer

Cluster analysis is the technique that aims to group a set of objects in such a way that objects in the same group (called a cluster) are more similar to each other than to those in other groups. This is used for exploratory data analysis to find natural groupings in data.

Question 9

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.

Accepted Answer

The description matches single linkage clustering, where the distance between two clusters is defined as the shortest distance between any single member of one cluster and any single member of another cluster.

Question 10

Sendstars is a package delivering company that recently made a study on its customer retention and service renewal metrics. They found that most customers defected from using Sendstars' services due to customer dissatisfaction stemming from delivery personnel being rude or ill-mannered. To curb this issue, Sendstars gave special training to its employees in customer service. Which of the following data mining approaches did Sendstars employ when they decided to train their employees in customer care based on the study?

Accepted Answer

Sendstars used cause-and-effect modeling to identify the reason behind customer defection (rude or ill-mannered delivery personnel) and then took corrective action (special training in customer service) to address the issue.

Question 11

Which of the following is true of hierarchical clustering?

Accepted Answer

Hierarchical clustering builds clusters in a stepwise manner, either by starting with all data points as individual clusters and merging them (agglomerative approach) or by starting with one cluster containing all data points and dividing it (divisive approach). This process does not partition all data into clusters in a single step, but rather incrementally.

Question 12

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

Accepted Answer

In the context of a credit approval decision, the categorical variable of interest is the outcome variable, which is whether the credit is rejected or accepted. This is a categorical variable because it divides the data into distinct categories (reject or accept) without any inherent order. Age, income, and revolving balance are all examples of numerical variables, not categorical.

Question 13

Which of the following is included in the data mining approach of Cluster Analysis?

Accepted Answer

Cluster Analysis is focused on identifying groups or clusters within a dataset where the elements within each group are similar to each other but different from those in other groups. This approach is used to discover natural groupings or patterns in data.

Question 14

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.

Accepted Answer

Cause-and-effect modeling is focused on identifying and understanding the relationships between variables that influence business outcomes, such as profitability and customer satisfaction, making it the correct choice for this description.

Question 15

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

Accepted Answer

Divisive clustering methods start with all objects in one cluster and then iteratively divide them into finer groupings, unlike agglomerative methods which start with each object in its own cluster and merge them into larger clusters.

Question 16

Which of the following is true of the value of k in the k-Nearest Neighbors algorithm?

Accepted Answer

The value of k in the k-Nearest Neighbors algorithm affects the bias-variance tradeoff. A very large k value can lead to a model that is too generalized, essentially introducing bias into the classification decisions by making the classification outcome too dependent on the overall distribution of the data, rather than on the nearest neighbors. This is because as k increases, the model becomes more stable and less sensitive to noise in the data, but it may also become too simplistic to capture the nuances in the data, leading to a biased model.

Question 17

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?

Accepted Answer

The Euclidean distance between two points in a right triangle is represented by the length of the hypotenuse, as it directly connects the two points, following the Pythagorean theorem.

Question 18

U-botit.com is an electronic commerce company that sells music online. It keeps a tab of what genre of music their registered customers buy. If u-botit.com were to use the data mining approach of association, which of the following actions would it take?

Accepted Answer

The association approach in data mining involves finding relationships or associations between different items or datasets. By sending recommendations to customers based on their buying habits, u-botit.com would be leveraging these associations to potentially increase sales and enhance customer experience.

Question 19

The effectiveness of a classification rule can be judged making a probability of misclassification errors and summarizing the results in a .

Accepted Answer

A classification matrix, also known as a confusion matrix, is a tool used to summarize the performance of a classification algorithm by showing the correct and incorrect predictions made by the model, thus allowing for the assessment of misclassification errors.

Question 20

The algorithm is a classification scheme that attempts to find records in a database that are similar to one we wish to classify.

Accepted Answer

The k-Nearest Neighbors (k-NN) algorithm is a classification scheme that identifies the k closest neighbors to the input data and classifies the new data point based on the majority class among those neighbors. This process inherently involves finding records (or data points) in the database that are similar to the one being classified.

Quiz 10: Introduction to Data Mining