Question 1

Divisive clustering method is different from agglomerative clustering methods in that divisive clustering methods .
A) can only have a pair of subjects in each cluster
B) separate objects into a particular cluster in one step
C) separate n objects successively into finer groupings
D) can only have a single subject in each cluster

Accepted Answer

Divisive clustering methods start with all objects in one cluster and successively divide them into finer groupings until each object is in its own cluster. This is the opposite of agglomerative clustering methods, which start with each object in its own cluster and successively merge them into larger groupings. Option A and D are incorrect because there is no restriction on the number of subjects in each cluster. Option B is incorrect because divisive clustering does not separate objects into a particular cluster in one step, but rather divides them into progressively smaller clusters.

Question 2

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.
A) Association rule mining
B) Discriminant analysis
C) Cluster analysis
D) Logistic regression

Accepted Answer

Cluster analysis is specifically designed to group observations or objects based on similarity. The other techniques listed are not primarily focused on grouping or segmenting objects in this manner.

Question 3

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.
A) Ward's linkage clustering
B) single linkage clustering
C) divisive clustering
D) average group linkage clustering

Accepted Answer

The method described is single linkage clustering, where the distance between clusters is defined as the minimum distance between any two points belonging to different clusters.

Question 4

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?
A) send recommendations to customers based on their buying habits
B) conduct surveys to customers to gauge customer satisfaction
C) classify the customers based on the genre of music they listen to
D) provide discounts to certain genre buyers where sales are less

Accepted Answer

The association data mining approach is used to identify patterns and relationships between variables. In this case, u-botit.com wants to use this approach to analyze the buying habits of their customers and identify which genres are commonly purchased together. This information can then be used to make personalized recommendations to customers based on their buying habits. This would help to increase customer satisfaction and loyalty, as well as boost sales for u-botit.com. Therefore, the best choice is A, to send recommendations to customers based on their buying habits.

Question 5

The effectiveness of a classification rule can be judged making a probability of misclassification errors and summarizing the results in a .
A) classification matrix
B) classification hierarchy
C) dendogram
D) classification algorithm

Accepted Answer

A classification matrix (also known as a confusion matrix) is used to evaluate the effectiveness of a classification rule by summarizing the number of correct and incorrect classifications for each class. It displays the predicted classes against the true classes, making it easy to see where misclassifications are occurring and to calculate the probability of misclassification errors. The other options (classification hierarchy, dendogram, classification algorithm) are not appropriate for evaluating the effectiveness of a classification rule.

Question 6

Which of the following formulas calculates the Euclidean distance between X and Y? 
A) $ \sqrt{\left(x_{1}-x_{2}\right)^{2}+\left(x_{2}-\gamma_{2}\right)^{2}+\ldots+\left(x_{n}-\gamma_{n}\right)^{2}} $
B) $ \sqrt{\left(x_{1}+\gamma_{1}\right)+\left(x_{2}+\gamma_{2}\right)+\ldots+\left(x_{n}+\gamma_{n}\right)} $
C) $ \sqrt{\left(x_{1}-\gamma_{1}\right)^{2}+\left(x_{2}-\gamma_{2}\right)^{2}+\ldots+\left(x_{n}-\gamma_{n}\right)^{2}} $
D) $ \sqrt{\left(x_{n}-\gamma_{n}\right)^{2}} $

Accepted Answer

The formula for Euclidean distance between two points with n coordinates is given by
$$\sqrt{\left(x_{1}-y_{1}\right)^{2}+\left(x_{2}-y_{2}\right)^{2}+\cdots+\left(x_{n}-y_{n}\right)^{2}}$$
Here, X and Y represent two n-dimensional points, so the correct formula is
$$\sqrt{\left(x_{1}-\gamma_{1}\right)^{2}+\left(x_{2}-\gamma_{2}\right)^{2}+\ldots+\left(x_{n}-\gamma_{n}\right)^{2}}$$
which matches option C.

Question 7

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.
A) association
B) reduction
C) cause-and-effect modeling
D) classification

Accepted Answer

The data mining approach described here is cause-and-effect modeling, which seeks to identify the factors that cause a particular outcome in order to predict or influence that outcome. The other options (association, reduction, and classification) focus on identifying patterns or groupings within data, but do not necessarily seek to explain or predict the relationship between variables in the way that cause-and-effect modeling does.

Question 8

Which of the following features of classification, used in Excel, for a particular database will necessarily be coded to a certain value?
A) categorical variables
B) non-numerical variables
C) predictor variables
D) numerical variables

Accepted Answer

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

Question 9

Which of the following data sets provides the most realistic estimate of the performance of a model on completely unseen data?
A) validation data set
B) test data set
C) training data set
D) linear regression data set

Accepted Answer

The test data set provides the most realistic estimate of the performance of a model on completely unseen data because it is a subset of the data that was not used for training or model selection. Therefore, it represents how the model will perform on new, unseen data, providing a more honest evaluation of the model's efficacy.

Question 10

Which of the following is a definition of distance between two clusters in a complete linkage clustering?
A) the average of distances between all pairs of objects, where each pair is made up of one object from each group
B) the distance between the most distant pair of objects, one from each group
C) the sum of squares of the distance between clusters
D) the distance between the value of the shortest link between the clusters

Accepted Answer

In a complete linkage clustering, the distance between two clusters is defined as the distance between the most distant pair of objects, one from each group. This is because complete linkage clustering seeks to minimize the maximum distance between objects in each cluster, so it makes sense to define the distance between clusters as the distance between their most distant members.

Question 11

Which of the following is true of a training data set?
A) They are primarily used to fine-tune models.
B) They provide the most realistic estimate for a model's performance.
C) They are used to build models where the data is unknown.
D) They have known outcomes.

Accepted Answer

A training data set is a set of data used to build and train a model. It typically includes inputs and corresponding known outcomes, allowing the model to learn from the data and make predictions on new, unseen data. Therefore, option D is the correct answer. Options A, B and C are incorrect as they do not accurately describe the main purpose of a training data set.

Question 12

Which of the following is true of hierarchical clustering?
A) All clusters must have the same number of data.
B) No single cluster can have all objects
C) The data are not partitioned into a particular cluster in a single step.
D) All clusters must have more than one object in it.

Accepted Answer

Hierarchical clustering is a method of clustering data where the data are not partitioned into a particular cluster in a single step. Instead, clusters are formed incrementally by merging smaller clusters together to form larger clusters. This process continues until all the data are in a single cluster or until some stopping criterion is met. Therefore, option C is true. Options A, B, and D are not true.

Question 13

Spam filtering for e-mails can be seen as an example of which of the following types of approaches of data mining?
A) reduction
B) association
C) cause-and-effect modeling
D) classification

Accepted Answer

Spam filtering for e-mails involves classifying the e-mails as either spam or not spam, which is a typical use case for classification in data mining.

Question 14

In classification, which of the following would be considered as a categorical variable of interest for a credit approval decision for a requester?
A) age of the requester
B) income of the requester
C) revolving balance of the requester
D) reject or accept credit approval

Accepted Answer

Out of the given variables, only "reject or accept credit approval" would be considered as a categorical variable of interest for a credit approval decision for a requester. The other variables (age, income, revolving balance) are all continuous variables and would not be categorized.

Question 15

Which of the following is true of cluster analysis?
A) It is a cause-and-modeling type of analytic model.
B) It does not provide a definitive answer from analyzing the data.
C) It is primarily a prescriptive analytical method.
D) It uses clustered data that are not affected by the specific method used.

Accepted Answer

Cluster analysis is a descriptive method that is used to identify patterns and groupings in data. However, it does not provide a definitive answer since different methods can produce different results.

Question 16

Which of the following is the first stage of joining clusters in agglomerative hierarchical clustering?
A) by separating clusters into finer groups
B) by joining two clusters farthest away from each other
C) by joining two clusters that are not at a Euclidean distance
D) by joining two clusters that are closest to each other

Accepted Answer

The first stage of joining clusters in agglomerative hierarchical clustering is by joining two clusters that are closest to each other. This is because the algorithm starts with each data point as its own cluster and then progressively merges the two most similar clusters until all points belong to a single cluster.

Question 17

Which of the following uses the sum of squares between the objects in the cluster when measuring their distances?
A) divisive clustering
B) average group linkage clustering
C) Ward's hierarchical clustering
D) single linkage clustering

Accepted Answer

Ward's hierarchical clustering uses the sum of squares between the objects in the cluster when measuring their distances.

Question 18

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?
A) the hypotenuse
B) the small leg
C) the long leg
D) the average of the sum of both the legs

Accepted Answer

The Euclidean distance between two objects in a cluster is calculated using Pythagorean theorem, which represents a right triangle. The hypotenuse of the right triangle represents the Euclidean distance between two objects of a cluster.

Question 19

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?
A) association
B) cause-and-effect modeling
C) classification
D) reduction

Accepted Answer

Sendstars used cause-and-effect modeling to identify the root cause of customer defection and to determine that the behavior of delivery personnel was the primary cause. They then used this information to develop a solution, which was providing customer service training to their employees.

Question 20

Which of the following is included in the data mining approach of data exploration and reduction?
A) analyzing data to predict how to classify a new data element
B) identifying groups in which the elements of the groups are in some way similar
C) creating rules for target marketing based on association of variables
D) developing analytic models to describe the relationship between metrics

Accepted Answer

Data exploration and reduction often involve identifying patterns or groups within the data, such as clustering, where similar data elements are grouped together.

Quiz 10: Introduction to Data Mining

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

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.

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.

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?

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

Which of the following formulas calculates the Euclidean distance between X and Y?

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.

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

Which of the following data sets provides the most realistic estimate of the performance of a model on completely unseen data?

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

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

Which of the following is true of hierarchical clustering?

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

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 true of cluster analysis?

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

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

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?

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