Data Mining Chapter 1
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.
- Multiple choice questions
- Score your understanding of data mining
- Learn as you go with instant feedback
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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