Data mining Mock Test Series 3, Free Data mining Online Test Series 3rd
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Data mining Mock Test Series 3, Free Data mining Online Test Series 3rd. Data mining Online Test 3 Question and Answers 2019. Data mining Test 3 Free Mock Test 2019. Data mining is a powerful new technology with great potential to help companies focus on the most important information in the data they have collected about the behavior of their customers and potential customers. It discovers information within the data that queries and reports can’t effectively reveal Now Test your self for “Data mining Online Test in English” Exam by using below quiz…
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Question 1 of 20
1. Question
Continuous Variable is known as
Correct
Incorrect

Question 2 of 20
2. Question
Which of the following Variable measured or their values defined ,using one of two kinds of Nonmetric scales
Correct
Discrete variables are also called qualitative variables. Such variables are measured, or their values defined, using one of two kinds of nonmetric scales – nominal or ordinal. A nominal scale is an orderless scale, which uses different symbols, characters, and numbers to represent the different states of the variable being measured.
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Discrete variables are also called qualitative variables. Such variables are measured, or their values defined, using one of two kinds of nonmetric scales – nominal or ordinal. A nominal scale is an orderless scale, which uses different symbols, characters, and numbers to represent the different states of the variable being measured.

Question 3 of 20
3. Question
A_______ is a model evaluation technique which is collection of methods used to examine the underlying constructs influence of the response of variables
Correct
Factor analysis is a model evaluation technique. It is a collection of methods used to examine the underlying constructs’ influence of the responses of variables. It is a model evaluation technique which is a collection of methods used to examine the underlying constructs influence of the response of variables.
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Factor analysis is a model evaluation technique. It is a collection of methods used to examine the underlying constructs’ influence of the responses of variables. It is a model evaluation technique which is a collection of methods used to examine the underlying constructs influence of the response of variables.

Question 4 of 20
4. Question
Which of the following analysis representing data using orthogonal vectors so that voluminous data can be projected on a smaller space.
Correct
The principle component analysis (PCA) aims at representing data using orthogonal vectors so that the original voluminous data can be projected on a smaller space. It differs from attribute selection strategies in that it creates a new and alternative set of variables (attributes) that capture the meaning of database. PCA allows normalization to avoid domination in the process of data compression.
Incorrect
The principle component analysis (PCA) aims at representing data using orthogonal vectors so that the original voluminous data can be projected on a smaller space. It differs from attribute selection strategies in that it creates a new and alternative set of variables (attributes) that capture the meaning of database. PCA allows normalization to avoid domination in the process of data compression.

Question 5 of 20
5. Question
Which are the following applications of clustering in data mining
Correct
Cluster analysis or clustering is the task of grouping a set of objects in such a way that objects in the same group (called cluster) are more similar (in some sense or another) to each other than to those in other groups (clusters). It is a main task of exploratory data mining, and a common technique for statistical data analysis used in many fields, including machine learning, pattern recognition, image analysis, information retrieval, and bioinformatics.
Incorrect
Cluster analysis or clustering is the task of grouping a set of objects in such a way that objects in the same group (called cluster) are more similar (in some sense or another) to each other than to those in other groups (clusters). It is a main task of exploratory data mining, and a common technique for statistical data analysis used in many fields, including machine learning, pattern recognition, image analysis, information retrieval, and bioinformatics.

Question 6 of 20
6. Question
What do you mean be MLP in data mining
Correct
A multilayer perceptron (MLP) is a feedforward artificial neural network model that maps sets of input data onto a set of appropriate outputs.
Incorrect
A multilayer perceptron (MLP) is a feedforward artificial neural network model that maps sets of input data onto a set of appropriate outputs.

Question 7 of 20
7. Question
Performance of matching between user query and document representation is called
Correct
Performance of matching between user query and document representation is called Evaluation.
Incorrect
Performance of matching between user query and document representation is called Evaluation.

Question 8 of 20
8. Question
A__________ technique to reduce the redundancies in data representation in order to decrease data storage requirements.
Correct
A data compression technique to reduce the redundancies in data representation in order to decrease data storage requirements and hence, communication costs when transmitted through a communication network. Reducing the storage requirement is equivalent to increasing the capacity of the storage medium and hence communication bandwidth.
Incorrect
A data compression technique to reduce the redundancies in data representation in order to decrease data storage requirements and hence, communication costs when transmitted through a communication network. Reducing the storage requirement is equivalent to increasing the capacity of the storage medium and hence communication bandwidth.

Question 9 of 20
9. Question
How much size required to high quality audio signal for digital representation and storage.
Correct
Incorrect

Question 10 of 20
10. Question
What is data mining?
Correct
Data mining is the computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database systems. It is an interdisciplinary subfield of computer science. The overall goal of the data mining process is to extract information from a data set and transform it into an understandable structure for further use.
Incorrect
Data mining is the computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database systems. It is an interdisciplinary subfield of computer science. The overall goal of the data mining process is to extract information from a data set and transform it into an understandable structure for further use.

Question 11 of 20
11. Question
________________stores data in a summarized version
Correct
A data cube stores data in a summarized version which helps in a faster analysis of data. The data is stored in such a way that it allows reporting easily.
Incorrect
A data cube stores data in a summarized version which helps in a faster analysis of data. The data is stored in such a way that it allows reporting easily.

Question 12 of 20
12. Question
Which of the following fields below typically make use of Data Mining techniques?
Correct
Data Mining as an analytic process designed to explore data (usually large amounts of – typically business or market related – data) in search for consistent patterns and/or systematic relationships between variables, and then to validate the findings by applying the detected patterns to new subsets of data.
Incorrect
Data Mining as an analytic process designed to explore data (usually large amounts of – typically business or market related – data) in search for consistent patterns and/or systematic relationships between variables, and then to validate the findings by applying the detected patterns to new subsets of data.

Question 13 of 20
13. Question
Which stage of data mining involves preparation and collection of data?
Correct
Incorrect

Question 14 of 20
14. Question
What is meant by discrete data?
Correct
Discreet data can be considered as defined or finite data. e.g. Mobile numbers. Only finite set of values are available.
Incorrect
Discreet data can be considered as defined or finite data. e.g. Mobile numbers. Only finite set of values are available.

Question 15 of 20
15. Question
Height, width comes under which type of data?
Correct
Continuous data can be considered as data which changes continuously and in an ordered fashion. e.g. age. Only real numbers are available. E.g. height, weight, length, temperature.
Incorrect
Continuous data can be considered as data which changes continuously and in an ordered fashion. e.g. age. Only real numbers are available. E.g. height, weight, length, temperature.

Question 16 of 20
16. Question
A decision tree is a tree in which every node is either a ________________ or a decision node
Correct
A decision tree is a tool that uses a tree like graph to model decisions and consequences to help managers incorporate uncertainty in valuations. A decision tree is a tree in which every node is either a leaf node or a decision node. A leaf node indicates the value of the target attribute (class) of examples.
Incorrect
A decision tree is a tool that uses a tree like graph to model decisions and consequences to help managers incorporate uncertainty in valuations. A decision tree is a tree in which every node is either a leaf node or a decision node. A leaf node indicates the value of the target attribute (class) of examples.

Question 17 of 20
17. Question
What is the Naive Bayes Algorithm used for?
Correct
Naive Bayes algorithm is a classification technique based on Bayes’ Theorem with an assumption of independence among predictors. In simple terms, a Naive Bayes classifier assumes that the presence of a particular feature in a class is unrelated to the presence of any other feature. Naive Bayes model is easy to build and particularly useful for very large data sets. Along with simplicity, Naive Bayes is known to outperform even highly sophisticated classification methods. It is used for estimating the probability of a class value during classification & prediction and generating mining models.
Incorrect
Naive Bayes algorithm is a classification technique based on Bayes’ Theorem with an assumption of independence among predictors. In simple terms, a Naive Bayes classifier assumes that the presence of a particular feature in a class is unrelated to the presence of any other feature. Naive Bayes model is easy to build and particularly useful for very large data sets. Along with simplicity, Naive Bayes is known to outperform even highly sophisticated classification methods. It is used for estimating the probability of a class value during classification & prediction and generating mining models.

Question 18 of 20
18. Question
Which of the following can be closely associated with Time Series algorithm?
Correct
Time series analysis comprises methods for analyzing time series data in order to extract meaningful statistics and other characteristics of the data. Time series forecasting is the use of a model to predict future values based on previously observed values.
Incorrect
Time series analysis comprises methods for analyzing time series data in order to extract meaningful statistics and other characteristics of the data. Time series forecasting is the use of a model to predict future values based on previously observed values.

Question 19 of 20
19. Question
Which algorithm is used to find correlations among different attributes in a data set?
Correct
Association algorithms find correlations between different attributes in a dataset. The most common application of this kind of algorithm is for creating association rules, which can be used in a market basket analysis.
Incorrect
Association algorithms find correlations between different attributes in a dataset. The most common application of this kind of algorithm is for creating association rules, which can be used in a market basket analysis.

Question 20 of 20
20. Question
What is the nature of Quality of data?
Correct
Data quality is a perception or an assessment of data’s fitness to serve its purpose in a given context. Aspects of data quality include:
– Accuracy
– Completeness
– Update status
– Relevance
– Consistency across data sources
– Reliability
– Appropriate presentation
– AccessibilityIncorrect
Data quality is a perception or an assessment of data’s fitness to serve its purpose in a given context. Aspects of data quality include:
– Accuracy
– Completeness
– Update status
– Relevance
– Consistency across data sources
– Reliability
– Appropriate presentation
– Accessibility