Data Mining Chapter 1

An educational illustration depicting data mining concepts, featuring elements like databases, algorithms, and visual representations of data patterns, in a modern and engaging design.

Data Mining Mastery Quiz

Test your knowledge of data mining concepts and techniques with our comprehensive quiz! This quiz features 24 questions covering key topics from the first chapter of data mining, including clustering, classification, and the knowledge discovery process.

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24 Questions6 MinutesCreated by MiningMaster42

Which of the following refers to the problem of finding abstracted patterns (or structures) in the unlabeled data?

Supervised learning

Unsupervised learning

Hybrid learning

Reinforcement learning

Which one of the following refers to querying the unstructured textual data?

Information access

Information update

Information retrieval

Information manipulation

Which of the following is an essential process in which the intelligent methods are applied to extract data patterns?

Warehousing

Text Mining

Data Selection

Data Mining

What is KDD in data mining?

Knowledge Discovery Database

Knowledge Discovery Data

Knowledge Data definition

Knowledge data house

What are the functions of Data Mining?

Association and correctional analysis classification

Prediction and characterization

Cluster analysis and Evolution analysis

All of the above

In the following given diagram, which type of clustering is used?

Hierarchal

Naive Bayes

Partitional

None of the above

Which of the following statements is incorrect about the hierarchal clustering?

The hierarchal type of clustering is also known as the HCA

The choice of an appropriate metric can influence the shape of the cluster

In general, the splits and merges both are determined in a greedy manner

All of the above

Which one of the following can be considered as the final output of the hierarchal type of clustering?

A tree which displays how the close thing are to each other

Assignment of each point to clusters

Finalize estimation of cluster centroids

None of the above

Which one of the following statements about the K-means clustering is incorrect?

The goal of the k-means clustering is to partition (n) observation into (k) clusters

K-means clustering can be defined as the method of quantization

The nearest neighbor is the same as the K-means

All of the above

Which one of the clustering technique needs the merging approach?

Partitioned

Naïve Bayes

Hierarchical

None of the above

The self-organizing maps can also be considered as the instance of _________ type of learning.

Supervised learning

Unsupervised learning

Missing data imputation

None of the above

Which of the following statement is true about the classification?

It is a measure of accuracy

It is a subdivision of a set

It is the task of assigning a classification

None of the above

Which of the following statements is correct about data mining?

It can be referred to as the procedure of mining knowledge from data

Data mining can be defined as the procedure of extracting information from a set of data

The procedure of data mining also involves several other processes like data cleaning, data transformation, and data integration

All of the above

Which of the following can be considered as the classification or mapping of a set or class with some predefined group or classes?

Data set

Data Characterization

Data Sub Structure

Data Discrimination

The analysis performed to uncover the interesting statistical correlation between associated -attributes value pairs are known as the _______.

Mining of association

Mining of correlation

Mining of clusters

All of the above

Which one of the following statements is not correct about the data cleaning?

It refers to the process of data cleaning

It refers to the transformation of wrong data into correct data

It refers to correcting inconsistent data

All of the above

Which one of the following correctly defines the term cluster?

Group of similar objects that differ significantly from other objects

Symbolic representation of facts or ideas from which information can potentially be extracted

Operations on a database to transform or simplify data in order to prepare it for a machine-learning algorithm

All of the above

Which of the following correctly refers the data selection?

A subject-oriented integrated time-variant non-volatile collection of data in support of management

The actual discovery phase of a knowledge discovery process

The stage of selecting the right data for a KDD process

All of the above

Which one of the following correctly refers to the task of the classification?

A measure of the accuracy, of the classification of a concept that is given by a certain theory

The task of assigning a classification to a set of examples

A subdivision of a set of examples into a number of classes

None of the above

Which of the following correctly defines the term "Hybrid"?

Approach to the design of learning algorithms that is structured along the lines of the theory of evolution.

Decision support systems that contain an information base filled with the knowledge of an expert formulated in terms of if-then rules.

Combining different types of method or information

None of these

Which of the following refers to the steps of the knowledge discovery process, in which the several data sources are combined?

Data selection

Data cleaning

Data transformation

Data integration

The term "DMQL" stands for _____

Data Marts Query Language

DBMiner Query Language

Data Mining Query Language

None of the above

Which one of the following issues must be considered before investing in data mining?

Compatibility

Functionality

Vendor consideration

All of the above

Which of the following also used as the first step in the knowledge discovery process?

Data selection

Data cleaning

Data transformation

Data integration

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