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Questions and Answers
What is one of the reasons for the enormous data growth in both commercial and scientific databases?
What is one of the reasons for the enormous data growth in both commercial and scientific databases?
- Decrease in data generation and collection technologies
- Lack of interest in data collection
- Advances in data generation and collection technologies (correct)
- Inefficient data storage technologies
Which company has Peta Bytes of web data, according to the text?
Which company has Peta Bytes of web data, according to the text?
- Apple
- Yahoo (correct)
- Microsoft
What is one of the examples of the competitive pressure mentioned in the text?
What is one of the examples of the competitive pressure mentioned in the text?
- Offer generic services to all customers
- Provide better, customized services for an edge in Customer Relationship Management (correct)
- Do not adapt to changing market trends
- Ignore customer needs
What is the new mantra (slogan) mentioned in the text?
What is the new mantra (slogan) mentioned in the text?
What is the purpose of data aggregation?
What is the purpose of data aggregation?
Why is sampling used in data mining?
Why is sampling used in data mining?
What is the main issue when merging data from heterogeneous sources?
What is the main issue when merging data from heterogeneous sources?
What is the purpose of data preprocessing?
What is the purpose of data preprocessing?
What is the purpose of attribute transformation in data preprocessing?
What is the purpose of attribute transformation in data preprocessing?
Why do statisticians use sampling?
Why do statisticians use sampling?
What is the purpose of feature subset selection in data preprocessing?
What is the purpose of feature subset selection in data preprocessing?
What is the purpose of discretization and binarization in data preprocessing?
What is the purpose of discretization and binarization in data preprocessing?
What is the primary purpose of data mining?
What is the primary purpose of data mining?
Which fields can benefit from data mining?
Which fields can benefit from data mining?
What are the sources of ideas for data mining?
What are the sources of ideas for data mining?
What are the tasks involved in data mining?
What are the tasks involved in data mining?
What does predictive modeling in data mining involve?
What does predictive modeling in data mining involve?
What are examples of classification tasks in data mining?
What are examples of classification tasks in data mining?
What are applications of classification tasks in data mining?
What are applications of classification tasks in data mining?
What is an example of an application involving sky objects in data mining?
What is an example of an application involving sky objects in data mining?
What is the aim of sky survey cataloging in data mining?
What is the aim of sky survey cataloging in data mining?
What do the diverse applications of data mining demonstrate?
What do the diverse applications of data mining demonstrate?
What is an example of regression in data mining?
What is an example of regression in data mining?
What is an application of cluster analysis in data mining?
What is an application of cluster analysis in data mining?
What is an example of association rule discovery in data mining?
What is an example of association rule discovery in data mining?
What is an application of deviation/anomaly/change detection in data mining?
What is an application of deviation/anomaly/change detection in data mining?
What are some motivating challenges in data mining?
What are some motivating challenges in data mining?
What does clustering in data mining aim to do?
What does clustering in data mining aim to do?
What is a practical application of clustering in data mining?
What is a practical application of clustering in data mining?
What is an example of association analysis in data mining?
What is an example of association analysis in data mining?
What is an application of deviation/anomaly/change detection in data mining?
What is an application of deviation/anomaly/change detection in data mining?
What does regression in data mining predict?
What does regression in data mining predict?
What is included in the dataset used for data mining?
What is included in the dataset used for data mining?
What are some key attributes used in classifying galaxies for data mining?
What are some key attributes used in classifying galaxies for data mining?
What type of data set represents data objects as points in a multi-dimensional space?
What type of data set represents data objects as points in a multi-dimensional space?
Which type of data involves a set of items in each record?
Which type of data involves a set of items in each record?
What is the term for data objects with considerably different characteristics than others?
What is the term for data objects with considerably different characteristics than others?
Which characteristic of data refers to the frequency of terms in each document?
Which characteristic of data refers to the frequency of terms in each document?
What type of data set consists of a collection of records with fixed attributes?
What type of data set consists of a collection of records with fixed attributes?
Which type of data quality problem refers to the modification of original values?
Which type of data quality problem refers to the modification of original values?
What type of data includes sequences of transactions and genomic sequence data?
What type of data includes sequences of transactions and genomic sequence data?
Which type of data set is represented as term vectors with the frequency of terms in each document?
Which type of data set is represented as term vectors with the frequency of terms in each document?
What characteristic of data refers to the number of attributes or features?
What characteristic of data refers to the number of attributes or features?
Which type of data set involves a generic graph, molecules, and webpages?
Which type of data set involves a generic graph, molecules, and webpages?
What type of data quality problem refers to data objects with considerably different characteristics than others?
What type of data quality problem refers to data objects with considerably different characteristics than others?
Which type of data set includes sequences of transactions and spatio-temporal data?
Which type of data set includes sequences of transactions and spatio-temporal data?
What are attributes also referred to as?
What are attributes also referred to as?
What is a collection of attributes also known as?
What is a collection of attributes also known as?
What are attribute values?
What are attribute values?
What distinguishes nominal attributes from ordinal attributes?
What distinguishes nominal attributes from ordinal attributes?
What distinguishes interval attributes from ratio attributes?
What distinguishes interval attributes from ratio attributes?
Who categorized attribute transformations?
Who categorized attribute transformations?
What type of values do discrete attributes have?
What type of values do discrete attributes have?
What characterizes binary attributes?
What characterizes binary attributes?
How are discrete attributes often represented?
How are discrete attributes often represented?
What type of values do continuous attributes have?
What type of values do continuous attributes have?
What may not capture all the properties of an attribute?
What may not capture all the properties of an attribute?
What is one of the examples of the competitive pressure mentioned in the text?
What is one of the examples of the competitive pressure mentioned in the text?
What is the new mantra (slogan) mentioned in the text for data collection?
What is the new mantra (slogan) mentioned in the text for data collection?
Which company has Peta Bytes of web data, according to the text?
Which company has Peta Bytes of web data, according to the text?
What is the primary reason for the enormous data growth in both commercial and scientific databases, as mentioned in the text?
What is the primary reason for the enormous data growth in both commercial and scientific databases, as mentioned in the text?
What is the purpose of data preprocessing in data mining?
What is the purpose of data preprocessing in data mining?
What is the main issue when merging data from heterogeneous sources?
What is the main issue when merging data from heterogeneous sources?
What does aggregation involve in data mining?
What does aggregation involve in data mining?
Why do statisticians use sampling?
Why do statisticians use sampling?
What is the aim of sampling in data mining?
What is the aim of sampling in data mining?
What characterizes the purpose of feature subset selection in data preprocessing?
What characterizes the purpose of feature subset selection in data preprocessing?
What is the purpose of discretization and binarization in data preprocessing?
What is the purpose of discretization and binarization in data preprocessing?
What is the purpose of attribute transformation in data preprocessing?
What is the purpose of attribute transformation in data preprocessing?
Which type of data set includes sequences of transactions and spatio-temporal data?
Which type of data set includes sequences of transactions and spatio-temporal data?
What is the term for data objects with considerably different characteristics than others?
What is the term for data objects with considerably different characteristics than others?
What is the main issue when merging data from heterogeneous sources?
What is the main issue when merging data from heterogeneous sources?
What type of data quality problem refers to the modification of original values?
What type of data quality problem refers to the modification of original values?
What is the characteristic of data that represents data objects as points in a multi-dimensional space?
What is the characteristic of data that represents data objects as points in a multi-dimensional space?
What type of data set involves a set of items in each record?
What type of data set involves a set of items in each record?
What are the important characteristics of data mentioned in the text?
What are the important characteristics of data mentioned in the text?
What does document data represent?
What does document data represent?
What does poor data quality have significant negative impacts on?
What does poor data quality have significant negative impacts on?
What are examples of data quality problems mentioned in the text?
What are examples of data quality problems mentioned in the text?
What type of data set consists of a collection of records with fixed attributes?
What type of data set consists of a collection of records with fixed attributes?
What does association analysis use?
What does association analysis use?
What is the primary focus of data mining?
What is the primary focus of data mining?
What is the aim of predictive modeling in data mining?
What is the aim of predictive modeling in data mining?
What are the applications of classification tasks in data mining?
What are the applications of classification tasks in data mining?
What is the main source of data for predicting the class of sky objects in astronomy?
What is the main source of data for predicting the class of sky objects in astronomy?
What is the primary aim of sky survey cataloging in data mining?
What is the primary aim of sky survey cataloging in data mining?
What are the key components that data mining draws ideas from?
What are the key components that data mining draws ideas from?
What are the two main types of data mining tasks mentioned?
What are the two main types of data mining tasks mentioned?
In data mining, what does classification involve?
In data mining, what does classification involve?
What is the primary focus of attribute transformation in data preprocessing?
What is the primary focus of attribute transformation in data preprocessing?
What is the aim of fraud detection in credit card transactions using data mining?
What is the aim of fraud detection in credit card transactions using data mining?
What is the primary function of data mining in the field of finance?
What is the primary function of data mining in the field of finance?
What is the primary application of data mining in the field of telecommunications?
What is the primary application of data mining in the field of telecommunications?
What is the primary aim of attribute transformation in data mining?
What is the primary aim of attribute transformation in data mining?
What differentiates nominal attributes from ordinal attributes?
What differentiates nominal attributes from ordinal attributes?
How are discrete attributes often represented?
How are discrete attributes often represented?
What characterizes binary attributes?
What characterizes binary attributes?
What is the purpose of discretization and binarization in data preprocessing?
What is the purpose of discretization and binarization in data preprocessing?
What distinguishes interval attributes from ratio attributes?
What distinguishes interval attributes from ratio attributes?
What is the aim of sky survey cataloging in data mining?
What is the aim of sky survey cataloging in data mining?
What type of values do continuous attributes have?
What type of values do continuous attributes have?
How are attributes often referred to collectively?
How are attributes often referred to collectively?
What does the type of an attribute depend on?
What does the type of an attribute depend on?
What is the purpose of attribute measurement in data mining?
What is the purpose of attribute measurement in data mining?
What is the aim of clustering in data mining?
What is the aim of clustering in data mining?
What is the primary aim of clustering in data mining?
What is the primary aim of clustering in data mining?
What is an application of deviation/anomaly/change detection in data mining?
What is an application of deviation/anomaly/change detection in data mining?
What type of data set includes 9 GB object catalog and a 150 GB image database?
What type of data set includes 9 GB object catalog and a 150 GB image database?
What characteristic of data refers to the frequency of terms in each document?
What characteristic of data refers to the frequency of terms in each document?
What are motivating challenges in data mining?
What are motivating challenges in data mining?
What is the aim of sky survey cataloging in data mining?
What is the aim of sky survey cataloging in data mining?
What is an example of association rule discovery in data mining?
What is an example of association rule discovery in data mining?
What is included in the dataset used for data mining?
What is included in the dataset used for data mining?
What does regression in data mining predict?
What does regression in data mining predict?
What are applications of cluster analysis in data mining?
What are applications of cluster analysis in data mining?
What is the term for data objects with considerably different characteristics than others?
What is the term for data objects with considerably different characteristics than others?
What characterizes binary attributes?
What characterizes binary attributes?
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Study Notes
Data Mining and Attributes Overview
- Attributes are also referred to as variables, fields, characteristics, or features, and collectively describe an object.
- Object, also known as record, point, case, sample, entity, or instance, is a collection of attributes.
- Attribute values are numbers or symbols assigned to an attribute, and a single attribute can be mapped to different attribute values.
- Different types of attributes include nominal, ordinal, interval, and ratio, each with distinct properties.
- The type of an attribute depends on its properties, such as distinctness, order, addition, and multiplication.
- Nominal attributes provide only enough information to distinguish one object from another, while ordinal attributes provide enough information to order objects.
- Interval attributes have meaningful differences between values, while ratio attributes have meaningful differences and ratios.
- Attributes can be transformed, and this categorization is due to S. S. Stevens.
- Discrete attributes have a finite or countably infinite set of values, while continuous attributes have real numbers as values.
- Asymmetric attributes, such as binary attributes, only consider the presence of non-zero attribute values.
- Discrete attributes are often represented as integer variables, while continuous attributes are typically represented as floating-point variables.
- The way an attribute is measured may not capture all its properties, as shown with different scales preserving different properties of length.
Data Mining: Key Concepts and Applications
- Data mining involves classifying galaxies, with attributes like image features and characteristics of light waves received.
- The dataset includes 72 million stars, 20 million galaxies, a 9 GB object catalog, and a 150 GB image database.
- Regression in data mining predicts continuous valued variables using linear or nonlinear models, with examples like sales prediction and time series analysis.
- Clustering in data mining finds groups of similar objects while maximizing inter-cluster distances and minimizing intra-cluster distances.
- Applications of cluster analysis include custom profiling for marketing, grouping documents for browsing, and clustering genes and proteins with similar functionality.
- Market segmentation and document clustering are practical applications of clustering in data mining.
- Association rule discovery predicts the occurrence of an item based on occurrences of other items, with applications in market-basket analysis and medical informatics.
- An example of association analysis is the identification of subspace differential coexpression patterns related to lung cancer.
- Deviation/anomaly/change detection in data mining is used in applications such as credit card fraud detection and identifying abnormal behavior in sensor networks.
- The motivating challenges in data mining include scalability, high dimensionality, heterogeneous and complex data, data ownership and distribution, and non-traditional analysis.
- Data mining involves the collection of data objects and their attributes, with examples like eye color and temperature.
- The text is from "Introduction to Data Mining, 2nd Edition" and "Advances in Knowledge Discovery and Data Mining, 1996" by Fayyad et al.
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