Data Mining Techniques Overview

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What is the purpose of concept hierarchy generation in data preprocessing?

To partition data into equal-frequency bins

To organize concepts hierarchically for easier data analysis (correct)

To automatically form concept hierarchies for both numeric and nominal data

To perform data smoothing by bin means

Which method involves recursively reducing data by replacing low level concepts with higher level concepts?

Data reduction

Data cleaning

Concept hierarchy generation (correct)

Data transformation

What is one of the major tasks in data preprocessing according to the text?

Data discretization

Data integration (correct)

Data smoothing

Data reduction

How are concept hierarchies usually formed in a data warehouse?

By explicitly specifying them by domain experts or designers Signup and view all the answers

What is the purpose of smoothing by bin means in data preprocessing?

To smoothen the data by using mean values within bins Signup and view all the answers

Which method involves preparing data for further analysis, like classification?

Discretization Signup and view all the answers

What is one possible reason for different attribute values of the same real-world entity from different sources?

Different data types Signup and view all the answers

How can redundant attributes in data integration be detected?

Covariance analysis Signup and view all the answers

Which statistical test is used in correlation analysis for nominal data?

Chi-square test Signup and view all the answers

What does a larger Χ2 value indicate in a Chi-square calculation?

Variables are positively correlated Signup and view all the answers

What does it mean if two variables are 'correlated' according to the text?

They are independent Signup and view all the answers

What does the correlation coefficient measure in correlation analysis for numeric data?

The relationship between two variables Signup and view all the answers

What does simple linear regression involve?

Finding the best line to fit two attributes to predict one another Signup and view all the answers

What is the purpose of outlier analysis in handling noisy data?

Detecting and handling values that fall outside of clusters Signup and view all the answers

In multiple linear regression, what does the error term represent?

Describes how the dependent variable is related to the independent variables Signup and view all the answers

What is one of the factors affecting data discrepancies mentioned in the text?

Respondents not wanting to divulge information Signup and view all the answers

How does smoothing by bin means handle noisy data?

Each value in a bin is replaced by the mean value of the bin Signup and view all the answers

'Data decay' refers to which factor affecting data discrepancies?

Outdated addresses Signup and view all the answers

What is the purpose of data compression in data mining?

To apply transformations and obtain a reduced representation of the original data Signup and view all the answers

Which of the following sampling methods involves selecting objects without removing them from the population?

Sampling with replacement Signup and view all the answers

What is the key principle behind sampling in data mining?

Choosing a representative subset of the data Signup and view all the answers

Which type of sampling is used when drawing samples from each partition proportionally?

Stratified sampling Signup and view all the answers

What is the purpose of data transformation in data preprocessing?

To map values of an attribute to new replacement values Signup and view all the answers

What does discretization in data preprocessing involve?

Dividing the range of a continuous attribute into intervals Signup and view all the answers

What is the purpose of data reduction?

To compress data and reduce dimensionality Signup and view all the answers

What problem does data transformation and discretization aim to solve?

Normalizing and generating concept hierarchies Signup and view all the answers

Which reference discusses declarative data cleaning?

H.Galhardas, D.Florescu, D.Shasha, E.Simon, and C.-A.Saita Signup and view all the answers

In data integration from multiple sources, what is the entity identification problem focused on?

Identifying unique entities across sources Signup and view all the answers

Which aspect is addressed in the reference by J.E.Olson?

Data Quality Signup and view all the answers

What does the reference by V.Raman and J.Hellerstein focus on?

Interactive framework for data cleaning Signup and view all the answers