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Data Mining

Description: Data Mining Databases
Number of Questions: 16
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Tags: Data Mining Databases
Attempted 0/16 Correct 0 Score 0

Which of the following levels of analysis is a non-linear predictive model that is learnt through training and that resembles biological neural networks in structure?

  1. Decision trees

  2. Genetic algorithm

  3. Artificial neural network

  4. Data visualization


Correct Option: C
Explanation:

This level of analysis is a non-linear predictive model that is learnt through training and that resembles biological neural networks in structure.

____________ is the automation of a learning process and learning is tantamount to the construction of rules based on observation of environmental states and transition.

  1. Statistics

  2. Machine learning

  3. Inductive learning

  4. None of these


Correct Option: B
Explanation:

Machine learning is the automation of a learning process and learning is tantamount to the construction of rules based on observation of environmental states and transition.

Which of the following categories of rules permits no exception so that each object of Left Hand Side (LHS) must be an element of Right Hand Side (RHS)?

  1. Strong rule

  2. Probabilistic rule

  3. Exact rule

  4. None of these


Correct Option: C
Explanation:

This category of rules permits no exception so that each object of Left Hand Side (LHS) must be an element of Right Hand Side (RHS).

Which of the following is a data cleansing stage where certain information is removed which is deemed unnecessary and may slow down queries?

  1. Transformation

  2. Preprocessing

  3. Data mining

  4. None of these


Correct Option: B
Explanation:

This is the data cleansing stage where certain information is removed, which is deemed unnecessary and may slow down queries.

Which of the following involves grouping data together based on a set of similarities predefined by the analyst before the exercise begins?

  1. Clustering

  2. Sequential discovery

  3. Classification

  4. None of these


Correct Option: C
Explanation:

Classification involves grouping data together based on a set of similarities pre-defined by the analyst before the exercise begins.

____________ attempts to find patterns between events that occur in a progression over a period of time.

  1. Clustering

  2. Sequential discovery

  3. Classification

  4. None of these


Correct Option: B
Explanation:

Sequential discovery attempts to find patterns between events that occur in a progression over a period of time.

Which of the following is the aggregation of data such as simple roll-ups or complex expressions involving inter-related data?

  1. Drill-Down

  2. Consolidation

  3. Slicing and dicing

  4. None of these


Correct Option: B
Explanation:

This OLAP database servers analytical involves the aggregation of data such as simple roll-ups or complex expressions, involving inter-related data.

________ refers to the ability to look at the database from different viewpoints.

  1. Consolidation

  2. Drill-Down

  3. Slicing and Dicing

  4. None of these


Correct Option: C
Explanation:

Slicing and Dicing refers to the ability to look at the database from different viewpoints.

____________ function is an operation against the set of records, which returns affinities or patterns that exists among the collection of items.

  1. Sequential pattern

  2. Clustering / segmentation

  3. Association

  4. None of these


Correct Option: C
Explanation:

An association function is an operation against this set of records, which returns affinities or patterns that exists among the collection of items.

Which of the following data mining applications finds associations among customer demographic characteristics?

  1. Banking

  2. Marketing

  3. Insurance and health care

  4. Transportation


Correct Option: B
Explanation:

This application find associations among customer demographic characteristics.

Which of the following characteristics of OLAP means that the system is targeted to deliver most responses to users within about five seconds with the simplest analyses taking no more than one second and very few taking more than 20 seconds?

  1. Fast

  2. Analysis

  3. Shared

  4. Multidimensional


Correct Option: A
Explanation:

This characteristic of OLAP means that the system is targeted to deliver most responses to users within about five seconds with the simplest analyses taking no more than one second and very few taking more than 20 seconds.

Which of the following data mining models is the one that discovers important information hidden in the data?

  1. Verification model

  2. DBTG model

  3. Discovery model

  4. None of these


Correct Option: C
Explanation:

This model in data mining is the one which discovers important information hidden in the data.

Which of the following involves maintaining up-to-date information in the Page Block Table (PBT)?

  1. Analysis

  2. Multidimensional

  3. Shared

  4. None of these


Correct Option: A
Explanation:

This means that the system can cope with any business logic and statistical analysis, which is relevant for the application and the user.  

 

In which of the following are data items grouped according to logical relationships or customer preferences?

  1. Classes

  2. Clusters

  3. Associations

  4. Sequential patterns


Correct Option: B
Explanation:

In this, data items are grouped according to logical relationships or customer preferences.

Which of the following is a simple knowledge representation used to classify a finite number of classes?

  1. Induction

  2. Decision trees

  3. Deduction

  4. None of these


Correct Option: B
Explanation:

This is a simple knowledge representation used to classify a finite number of classes.

Which of the following functions of data mining analyses a collection of records over a period of time to identify trends?

  1. Sequential / temporal patterns

  2. Association

  3. Clustering/segmentation

  4. None of these


Correct Option: A
Explanation:

This function of data mining analyses a collection of records over a period of time to identify trends.

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