# Data Mining Final Assessment

## Quiz by Yashaswini B M

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- Q1
Which of these is correct about data mining?

It is a procedure in which knowledge is mined from data.

It is a procedure using which one can extract information out of huge sets of data.

All of the above

It involves processes like Data Transformation, Data Integration, Data Cleaning.

30s - Q2
The classification or mapping of a class using a predefined class or group is called:

Data Set

Data Sub Structure

Data Characterisation

Data Discrimination

30s - Q3
What is the analysis conducted for uncovering some interesting statistical correlations between various associated-attribute-value pairs called?

None of the above

Mining of Correlations

Mining of Clusters

Mining of Association

30s - Q4
__________ are the data objects that don’t comply with the general model or behaviour of the available data:

Outlier Analysis

Prediction

Classification

Evolution Analysis

30s - Q5
The primary use of data cleaning is:

Correction of the data inconsistencies

Transformations for correcting the wrong data

Removing the noisy data

All of the above

30s - Q6
The classification of the Data Mining System consists of:

All of the above

Information Science

Database Technology

Machine Learning

30s - Q7
The class under study in Data Characterization is known as:

Initial Class

Target Class

Study Class

Final Class

30s - Q8
What does the letter K stand for in the K-nearest neighbour algorithm?

Number of neighbours that are used

Number of total observations in the dataset

Number of iterations

30s - Q9
What does noise mean in data mining?

Complex data

Repeated data

Random errors in the dataset

30s - Q10
Which process is used to rescaling the values of data into a range from 0 to 1?

Data normalisation

Data churning

Data preprocessing

30s - Q11
What is often considered the early methods to identify patterns in data?

Regression analysis

Bayes’s theorem

Cluster analysis

30s - Q12
Bayesian classifiers is

None of these

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.

A class of learning algorithm that tries to find an optimum classification of a set of examples usingthe probabilistic theory.

Any mechanism employed by a learning system to constrain the search space of a hypothesis

30s - Q13
Classification is

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

The task of assigning a classification to a set of examples

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

None of these

30s - Q14
Classification accuracy is

None of these

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

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

30s - Q15
Naive prediction is

A class of learning algorithms that try to derive a Prolog program from examples.

A prediction made using an extremely simple method, such as always predicting the same output.

None of these

A table with n independent attributes can be seen as an n- dimensional space

30s