Question 1

Which statement is not TRUE regarding a data mining task?
A)Clustering is a descriptive data mining task
B)Classification is a predictive data mining task
C)Regression is a descriptive data mining task
D)Deviation detection is a predictive data mining task

Accepted Answer

Regression is actually a predictive data mining task, not a descriptive one. It is used to predict a continuous outcome variable based on one or more predictor variables.

Question 2

Synonym for data mining is
A)Data Warehouse
B)Knowledge discovery in database
C)Business intelligence
D)OLAP

Accepted Answer

Knowledge discovery in database is a synonym for data mining.

Question 3

Which of the following is not a data mining task?
A)Feature Subset Detection
B)Association Rule Discovery
C)Regression
D)Sequential Pattern Discovery

Accepted Answer

Feature Subset Detection is not typically classified as a data mining task. Data mining tasks include processes like Association Rule Discovery, Regression, and Sequential Pattern Discovery, which are aimed at identifying patterns, trends, or relationships within data. Feature Subset Detection, on the other hand, is more related to the field of feature selection in machine learning, where the goal is to identify a subset of relevant features for model construction.

Question 4

Which of the following issue is considered before investing in Data Mining?
A)Functionality
B)Vendor consideration
C)Compatibility
D)All of the above

Accepted Answer

All of the mentioned issues, including functionality, vendor consideration, and compatibility, are important factors to consider before investing in data mining to ensure the solution meets business needs and integrates well with existing systems.

Question 5

Data independence means
A)Data is defined separately and not included in programs
B)Programs are not dependent on the physical attributes of data
C)Programs are not dependent on the logical attributes of data
D)Both (B) and (C)

Accepted Answer

Data independence refers to the capacity to change the schema at one level of a database system without having to change the schema at the next higher level. It includes both logical data independence (programs are not dependent on the logical structure of data) and physical data independence (programs are not dependent on the physical storage of data).

Question 6

A definition or a concept is if it classifies any examples as coming within the concept
A)Complete
B)Consistent
C)Constant
D)None of these

Accepted Answer

The answer of A definition or a concept is if...

Question 7

Which of the following activities is a data mining task?
A)Monitoring the heart rate of a patient for abnormalities
B)Extracting the frequencies of a sound wave
C)Predicting the outcomes of tossing a (fair) pair of dice
D)Dividing the customers of a company according to their profitability

Accepted Answer

The answer of Which of the following activities is a...

Question 8

Data Visualization in mining cannot be done using
A)Photos
B)Graphs
C)Charts
D)Information Graphics

Accepted Answer

Photos are not typically used for data visualization in mining as they do not represent data in a structured or analytical format like graphs, charts, or information graphics do.

Question 9

To detect fraudulent usage of credit cards, the following data mining task should be used
A)Outlier analysis
B)prediction
C)association analysis
D)feature selection

Accepted Answer

Outlier analysis is used to detect unusual patterns that do not conform to expected behavior, such as fraudulent credit card transactions.

Question 10

A definition or a concept is if it classifies any examples as coming within the concept
A)Complete
B)Consistent
C)Constant

Accepted Answer

The answer of A definition or a concept is if...

Question 11

Classification accuracy is
A)Subdivision of a set of examples into a number of classes
B)Measure of the accuracy, of the classification of a concept that is given by a certain theory
C)The task of assigning a classification to a set of examples

Accepted Answer

Classification accuracy is indeed a measure of how accurately a model or theory can classify or predict the correct class or category of instances, typically expressed as a percentage of correct predictions out of the total predictions made.

Question 12

Cluster is
A)Group of similar objects that differ significantly from other objects
B)Operations on a database to transform or simplify data in order to prepare it for a machine-learning algorithm
C)Symbolic representation of facts or ideas from which information can potentially be extracted

Accepted Answer

A cluster refers to a group of similar objects that are more similar to each other than to those in other groups or clusters. This concept is widely used in data analysis and machine learning for grouping data points or objects that share common characteristics.

Question 13

Assume you want to perform supervised learning and to predict number of newborns according to size of storks' population (http://www.brixtonhealth.com/storksBabies.pdf), it is an example of
A)Classification
B)Regression
C)Clustering
D)Structural equation modeling

Accepted Answer

Regression is used to predict a continuous outcome (number of newborns) based on one or more predictor variables (size of storks' population).

Question 14

Bayesian classifiers is
A)class of learning algorithm that tries to find an optimum classification of a set of examples using the probabilistic theory
B)Any mechanism employed by a learning system to constrain the search space of a hypothesis
C)An approach to the design of learning algorithms that is inspired by the fact that when people encounter new situations, they often explain them by reference to familiar experiences, adapting the explanations to fit the new situation
D)None of these

Accepted Answer

Bayesian classifiers are a class of learning algorithms that apply the probabilistic theory to find an optimal classification of examples. They use Bayes' theorem to predict the category of a sample, making them effective in various applications including spam detection and document classification.

Question 15

Background knowledge referred to
A)Additional acquaintance used by a learning algorithm to facilitate the learning process
B)A neural network that makes use of a hidden layer
C)It is a form of automatic learning
D)None of these

Accepted Answer

The answer of Background knowledge referred to
A)Additional acquaintance used by...

Question 16

Which of the following is finally produced by Hierarchical Clustering?
A)Final estimate of cluster centroids
B)tree showing how close things are to each other
C)assignment of each point to clusters
D)all of the mentioned

Accepted Answer

Hierarchical clustering produces a tree-like diagram known as a dendrogram, which shows how different objects are grouped together in a hierarchy, illustrating the closeness or similarity between objects.

Question 17

Which of the following combination is incorrect?
A)Continuous - euclidean distance
B)Continuous - correlation similarity
C)Binary - manhattan distance
D)None of the mentioned

Accepted Answer

All the combinations mentioned are correct in the context of data types and similarity/distance measures. Continuous data can use Euclidean distance and correlation similarity, and binary data can use Manhattan distance.

Question 18

Which of the following ways can be used to represent a graph?
A)Adjacency List and Adjacency Matrix
B)Incidence Matrix
C)Adjacency List, Adjacency Matrix as well as Incidence Matrix
D)No way to represent

Accepted Answer

Graphs can be represented using an Adjacency List, an Adjacency Matrix, and an Incidence Matrix, making all these methods valid for graph representation.

Question 19

Which of the following function is used for k-means clustering?
A)k-means
B)k-mean
C)heatmap
D)none of the mentioned

Accepted Answer

The correct function used for k-means clustering is "k-means". This function is commonly used in various programming languages and libraries for performing the k-means clustering algorithm.

Question 20

K-means is not deterministic and it also consists of number of iterations.

Accepted Answer

K-means clustering algorithm is not deterministic because the initial placement of centroids is usually random, which can lead to different results on different runs. It also iteratively updates the centroids until a stopping criterion is met, hence it consists of a number of iterations.

Quiz 5: Data Mining and Clustering: Key Concepts and Tasks

Which statement is not TRUE regarding a data mining task?

Synonym for data mining is

Which of the following is not a data mining task?

Which of the following issue is considered before investing in Data Mining?

Data independence means

A definition or a concept is if it classifies any examples as coming within the concept

Which of the following activities is a data mining task?

Data Visualization in mining cannot be done using

To detect fraudulent usage of credit cards, the following data mining task should be used

A definition or a concept is if it classifies any examples as coming within the concept

Classification accuracy is

Cluster is

Assume you want to perform supervised learning and to predict number of newborns according to size of storks' population (http://www.brixtonhealth.com/storksBabies.pdf) , it is an example of

Bayesian classifiers is

Background knowledge referred to

Which of the following is finally produced by Hierarchical Clustering?

Which of the following combination is incorrect?

Which of the following ways can be used to represent a graph?

Which of the following function is used for k-means clustering?

K-means is not deterministic and it also consists of number of iterations.