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What is Classification

Chapter 9
Advancing Educational Research With Emerging Technology
The process of splitting a continuous variable into groups or categories. On a map, the classified variable is presented as gradations of a color.
Published in Chapter:
Using Geographic Information Systems in Educational Research: A Beginner's Exercise
Elizabeth A. Gilblom (North Dakota State University, USA) and Hilla I. Sang (University of Nevada, Las Vegas, USA)
Copyright: © 2020 |Pages: 38
DOI: 10.4018/978-1-7998-1173-2.ch009
Abstract
The chapter introduces education researchers to geographic information systems (GIS) and the significant value of incorporating a geospatial perspective within research. The GIS approach to studying and presenting data incorporates geographic location and uses maps to visualize relationships for spatial and nonspatial variables, both of which enhance education research by visualizing local geographies. This chapter unfolds as a step-by-step guide that prepares researchers to identify the data needed for a GIS exercise, to collect or retrieve the data, clean and upload the data to ArcMap, georeferenced and symbolize the data, and interpret and present the results in a manuscript. After completing the exercise, researchers will have a basic understanding of ArcMap functionality and how integrating a geospatial perspective in educational research offers insights that may have otherwise been overlooked when using quantitative research methods alone.
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Chapter 1
Developing an Effective Classification Model for Medical Data Analysis
The process of assigning class label to unknown data points based on learned facts.
Published in Chapter: Developing an Effective Classification Model for Medical Data Analysis; From: Advanced Classification Techniques for Healthcare Analysis
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Chapter 8
Affectively Enhanced Subs: Visualization of Auditory Events With Color Scales and Animation
The process related to categorization, the process in which ideas and objects are recognized, differentiated, and understood. Most commonly used classifiers (algorithms) are K-nearest Neighbors (KNN), Hidden Markov Model (HMM), Gaussian Mixture Model (GMM), Support Vector Machines (SVM), and Artificial Neural Networks (ANN).
Published in Chapter: Affectively Enhanced Subs: Visualization of Auditory Events With Color Scales and Animation; From: Advanced Technologies and Standards for Interactive Educational Television: Emerging Research and Opportunities
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Chapter 2
Data Avalanche: Harnessing for Mobile Payment Fraud Detection Using Machine Learning
This a supervised learning where the input data is tagged with an output data. The goal of classification is to predict the output data based on the input data.
Published in Chapter: Data Avalanche: Harnessing for Mobile Payment Fraud Detection Using Machine Learning; From: Handbook of Research on Managing Information Systems in Developing Economies
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Chapter 5
Feature Selection Algorithm Using Relative Odds for Data Mining Classification
In data mining, classification is a supervised learning activity concerned about developing models that can accurately predict the class labels of vectors whose classes are unknown.
Published in Chapter: Feature Selection Algorithm Using Relative Odds for Data Mining Classification; From: Big Data Analytics for Sustainable Computing
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Chapter 10
Use of PCA Solution in Hierarchy and Case of Two Classes of Data Sets to Initialize Parameters for Clustering Function: An Estimation Method for Clustering Function in Classification Application
Classification is an application of pattern recognition by the assignment of the data instance with label. The assignment is realized by the measurement using certain dissimilarity metrics function.
Published in Chapter: Use of PCA Solution in Hierarchy and Case of Two Classes of Data Sets to Initialize Parameters for Clustering Function: An Estimation Method for Clustering Function in Classification Application; From: Advancements in Computer Vision Applications in Intelligent Systems and Multimedia Technologies
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Chapter 5
Of Paradigms, Theories, and Models: A Conceptual Hierarchical Structure for Communication Science and Technoself
Any practical or theoretical framework that helps to distinguish among categories, degrees, or dimensions of any human and theoretical enterprise.
Published in Chapter: Of Paradigms, Theories, and Models: A Conceptual Hierarchical Structure for Communication Science and Technoself; From: Handbook of Research on Technoself: Identity in a Technological Society
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Chapter 4
Predicting the Academic Performance of Students Using Utility-Based Data Mining
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Chapter 3
Deep Learning Models for Physiological Data Classification of Children During Computerized Auditory Tests: Deep Learning-Based Emotion Recognition in Child-Computer Interaction
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Chapter 17
Comparison of Machine Learning Algorithms in Predicting the COVID-19 Outbreak
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Chapter 18
Health Information System
Predicts the target class for each data points.
Published in Chapter: Health Information System; From: Handbook of Research on Healthcare Administration and Management
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Chapter 18
Automated Framework for Software Process Model Selection Based on Soft Computing Approach
A data mining algorithm that creates a step-by-step guide to determine the output of a new data instance.
Published in Chapter: Automated Framework for Software Process Model Selection Based on Soft Computing Approach; From: Handbook of Research on Fuzzy and Rough Set Theory in Organizational Decision Making
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Chapter 3
From Tf-Idf to Learning-to-Rank: An Overview
A supervised learning task where the ground truth labels are integer numbers.
Published in Chapter: From Tf-Idf to Learning-to-Rank: An Overview; From: Handbook of Research on Innovations in Information Retrieval, Analysis, and Management
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Chapter 29
Variable Importance Evaluation for Machine Learning Tasks
A typical data mining task in which cases of a dataset are divided into different classes or groups according to similarity or distance.
Published in Chapter: Variable Importance Evaluation for Machine Learning Tasks; From: Encyclopedia of Information Science and Technology, Third Edition
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Chapter 8
XHAC: Explainable Human Activity Classification From Sensor Data
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Chapter 17
A Novel Fuzzy Logic Classifier for Classification and Quality Measurement of Apple Fruit
Classification refers to as assigning a physical object or incident into one of a set of predefined categories.
Published in Chapter: A Novel Fuzzy Logic Classifier for Classification and Quality Measurement of Apple Fruit; From: Handbook of Research on Emerging Perspectives in Intelligent Pattern Recognition, Analysis, and Image Processing
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Chapter 51
Lative Logic Accomodating the WHO Family of International Classifications
Classification refers mainly to WHO’s reference classifications.
Published in Chapter: Lative Logic Accomodating the WHO Family of International Classifications; From: Encyclopedia of E-Health and Telemedicine
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Chapter 8
Detecting Bank Financial Fraud in South Africa Using a Logistic Model Tree
The established criteria or procedure to categorise or group together elements that are similar or dissimilar.
Published in Chapter: Detecting Bank Financial Fraud in South Africa Using a Logistic Model Tree; From: Applications of Machine Learning and Deep Learning for Privacy and Cybersecurity
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Chapter 9
Game Literacy: Assessing its Value for Both Classification and Public Perceptions of Games in a New Zealand Context
A classification is a statement about who is eligible to view a publication. In New Zealand, the Classification Office is responsible for classifying all publications that may be harmful and need to be restricted (e.g. R18) or banned.
Published in Chapter: Game Literacy: Assessing its Value for Both Classification and Public Perceptions of Games in a New Zealand Context; From: Handbook of Research on Improving Learning and Motivation through Educational Games: Multidisciplinary Approaches
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Chapter 3
A New Tree-Based Classifier for Satellite Images
It is a problem of identifying an appropriate class label for a new pixel (or observation) based on a training set of data whose class labels are known.
Published in Chapter: A New Tree-Based Classifier for Satellite Images; From: Encyclopedia of Business Analytics and Optimization
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Chapter 6
A Survey on Data Mining Techniques in Research Paper Recommender Systems
The action or process of categorizing or grouping something.
Published in Chapter: A Survey on Data Mining Techniques in Research Paper Recommender Systems; From: Research Data Access and Management in Modern Libraries
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Chapter 112
A Hybridized GA-Based Feature Selection for Text Sentiment Analysis
This is the technique used to separate the categorical values on the basis of their positivity and negativity.
Published in Chapter: A Hybridized GA-Based Feature Selection for Text Sentiment Analysis; From: Encyclopedia of Data Science and Machine Learning
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Chapter 19
Future Expectations About Big Data Analytics
It is a supervised method used in machine learning to classify the given input data.
Published in Chapter: Future Expectations About Big Data Analytics; From: Big Data Analytics Techniques for Market Intelligence
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Chapter 11
Acoustic Presence Detection in a Smart Home Environment
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Chapter 7
Wolf-Swarm Colony for Signature Gene Selection Using Weighted Objective Method
It is a process to categorize the objects so that they can be differentiated from others.
Published in Chapter: Wolf-Swarm Colony for Signature Gene Selection Using Weighted Objective Method; From: Nature-Inspired Algorithms for Big Data Frameworks
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Chapter 185
Text Mining
Objects are assigned to pre-defined classes based on similarity. Similar objects are assigned to the same class. The function defining similarity is given by examples for the assignment. These are objects which have been assigned to a class before. The algorithm needs to learn a function which reflects the class definition as determined by the learning examples.
Published in Chapter: Text Mining; From: Encyclopedia of Information Science and Technology, Third Edition
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Chapter 57
Data Mining for Business Analytics in Retail
Classification is a supervised machine learning technique which predicts the classification label of a given instance.
Published in Chapter: Data Mining for Business Analytics in Retail; From: Encyclopedia of Business Analytics and Optimization
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Chapter 11
Data Mining and Machine Learning Approaches in Breast Cancer Biomedical Research
It is a data mining function that assigns items in a collection to target categories or classes.
Published in Chapter: Data Mining and Machine Learning Approaches in Breast Cancer Biomedical Research; From: Sentiment Analysis and Knowledge Discovery in Contemporary Business
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Chapter 2
Machine Learning and Optimization Applications for Soft Robotics
Classification is a commonly applied supervised learning method that assigns one of the predefined classes to new instances.
Published in Chapter: Machine Learning and Optimization Applications for Soft Robotics; From: Design and Control Advances in Robotics
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Chapter 11
Mapping Artificial Emotions into a Robotic Face
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Chapter 9
Determination of Stability of Rock Slope Using Intelligent Pattern Recognition Techniques
It means to either attribute to a condition of stable or failure. A value of 1 is assigned to the stable condition of rock slope while a value of - 1 is assigned to the failure condition of rock slope.
Published in Chapter: Determination of Stability of Rock Slope Using Intelligent Pattern Recognition Techniques; From: Handbook of Research on Emerging Perspectives in Intelligent Pattern Recognition, Analysis, and Image Processing
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Chapter 9
Animal Activity Recognition From Sensor Data Using Ensemble Learning
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Chapter 2
An Uncertainty-Based Model for Optimized Multi-Label Classification
It is a process similar to clustering except that it comes under supervised learning in contrast to clustering, which comes under unsupervised learning approach.
Published in Chapter: An Uncertainty-Based Model for Optimized Multi-Label Classification; From: Handbook of Research on Swarm Intelligence in Engineering
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Chapter 13
Optimizing Learning Weights of Back Propagation Using Flower Pollination Algorithm for Diabetes and Thyroid Data Classification
Classification is a technique in which the data are grouped into a given number of classes on the basis of some similarity and constraints. The main aim of the classification technique is to shrink the measure of the error.
Published in Chapter: Optimizing Learning Weights of Back Propagation Using Flower Pollination Algorithm for Diabetes and Thyroid Data Classification; From: Mobile Devices and Smart Gadgets in Medical Sciences
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Chapter 5
Identification of Agricultural Crop Residues Using Non-Destructive Methods
?s a process related to categorization, the process in which ideas and objects are recognized, differentiated, and understood.
Published in Chapter: Identification of Agricultural Crop Residues Using Non-Destructive Methods; From: Applications of Image Processing and Soft Computing Systems in Agriculture
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Chapter 6
The Application of Big Data and Cloud Computing Among Smallholder Farmers in Sub-Saharan Africa
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Chapter 9
Big Data Analytics in Action: Examples
In machine learning and statistics, classification is the problem of identifying to which of a set of categories (sub-populations) a new observation belongs, on the basis of a training set of data containing observations (or instances) whose category membership is known.
Published in Chapter: Big Data Analytics in Action: Examples; From: Big Data Analytics for Entrepreneurial Success
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Chapter 18
Aspects of Visualization and the Grid in a Biomedical Context
Process by which image data is analyzed into ground-truth categories, such as tissue type.
Published in Chapter: Aspects of Visualization and the Grid in a Biomedical Context; From: Handbook of Research on Computational Grid Technologies for Life Sciences, Biomedicine, and Healthcare
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Chapter 15
Threat Detection in Cyber Security Using Data Mining and Machine Learning Techniques
The process by which an algorithm/model segregates the feature space into different classes.
Published in Chapter: Threat Detection in Cyber Security Using Data Mining and Machine Learning Techniques; From: Modern Theories and Practices for Cyber Ethics and Security Compliance
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Chapter 305
Developments of the Digital World of Remote Sensing and GIS, Their Comparison to, and the Importance of the Human Side of Information Reference Services
The process of classification identified and assigned each pixel of all channels of the multi-spectral images to a particular class or theme based on the statistical characteristics of the pixel brightness values known as spectral signatures.
Published in Chapter: Developments of the Digital World of Remote Sensing and GIS, Their Comparison to, and the Importance of the Human Side of Information Reference Services; From: Encyclopedia of Information Science and Technology, Third Edition
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Chapter 11
Insulin DNA Sequence Classification Using Levy Flight Bat With Back Propagation Algorithm
Classification is a technique in which the data are grouped into a given number of classes on the basis of some similarity and constraints. The main aim of the classification technique is to shrink the measure of the error.
Published in Chapter: Insulin DNA Sequence Classification Using Levy Flight Bat With Back Propagation Algorithm; From: Mobile Devices and Smart Gadgets in Medical Sciences
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Chapter 47
Classification and Recommendation With Data Streams
Is the task that assigns items to a set of classes.
Published in Chapter: Classification and Recommendation With Data Streams; From: Encyclopedia of Information Science and Technology, Fifth Edition
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Chapter 12
A Survey on Recent Recommendation Systems for the Tourism Industry
It is an act of discovering a function either model that defines and differentiates data concepts or classes for future prediction.
Published in Chapter: A Survey on Recent Recommendation Systems for the Tourism Industry; From: Accelerating Knowledge Sharing, Creativity, and Innovation Through Business Tourism
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Chapter 4
Towards a Classification Framework for Concepts of Innovation for and From Emerging Markets
A process in which ideas and objects (inter alia terms and theories) are recognized, differentiated, and understood.
Published in Chapter: Towards a Classification Framework for Concepts of Innovation for and From Emerging Markets; From: Responsible, Sustainable, and Globally Aware Management in the Fourth Industrial Revolution
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Chapter 10
Decision Support Proposal for Imbalanced Clinical Data
The purpose of classification is to predict which of the pre-labeled data groups similar data belong to.
Published in Chapter: Decision Support Proposal for Imbalanced Clinical Data; From: Handbook of Research on Applied Intelligence for Health and Clinical Informatics
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Chapter 30
Interpreting Brain Waves
The process of categorizing a set of observations into two or more categories and deciding to which of them a new observation belongs.
Published in Chapter: Interpreting Brain Waves; From: Handbook of Research on Machine Learning Innovations and Trends
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Chapter 4
Big Data Analytics: Educational Data Classification Using Hadoop-Inspired MapReduce Framework
A classification is allocation, categorization, and analysis of data according to its similarities.
Published in Chapter: Big Data Analytics: Educational Data Classification Using Hadoop-Inspired MapReduce Framework; From: Predictive Intelligence Using Big Data and the Internet of Things
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Chapter 27
Automated Technology Integrations for Customer Satisfaction Assessment
A process of recognizing patterns between different data based on certain relevant characteristic. Classification process could be supervised or unsupervised.
Published in Chapter: Automated Technology Integrations for Customer Satisfaction Assessment; From: Handbook of Research on Managing and Influencing Consumer Behavior
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Chapter 42
Class-Dependent Principal Component Analysis
A type of computational problems where the goal is to assign an observation or instance to one of known classes of data.
Published in Chapter: Class-Dependent Principal Component Analysis; From: Encyclopedia of Business Analytics and Optimization
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Chapter 1
Segmented Dynamic Time Warping: A Comparative and Applicational Study
A supervised learning method in machine learning, which is used to identify unknown instance categories based on known instances.
Published in Chapter: Segmented Dynamic Time Warping: A Comparative and Applicational Study; From: Emerging Technologies and Applications in Data Processing and Management
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Chapter 113
Bio-Inspired Algorithms for Feature Selection: A Brief State of the Art
A process of putting objects on previously defined classes (supervised) or not defined (unsupervised) according to defined attributes by using specific algorithms.
Published in Chapter: Bio-Inspired Algorithms for Feature Selection: A Brief State of the Art; From: Encyclopedia of Data Science and Machine Learning
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Chapter 14
Heart Sound Data Acquisition and Preprocessing Techniques: A Review
The process of systematic arrangement in groups or categories according to established criteria.
Published in Chapter: Heart Sound Data Acquisition and Preprocessing Techniques: A Review; From: Handbook of Research on Advancements of Artificial Intelligence in Healthcare Engineering
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Chapter 17
Deep-Auto Encoders for Detecting Credit Card Fraud
A data mining task that builds a predictive model to predict the target label of an unknown test record.
Published in Chapter: Deep-Auto Encoders for Detecting Credit Card Fraud; From: Handbook of Research on the Significance of Forensic Accounting Techniques in Corporate Governance
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Chapter 9
Crow-ENN: An Optimized Elman Neural Network with Crow Search Algorithm for Leukemia DNA Sequence Classification
Classification is kind of supervised machine learning which is used to classify every element in a dataset into one of the predefined set of groups or classes based on some similarities or homology. There are many machine learning techniques used for classification like Decision Trees, Support Vector Machine, Artificial Neural Networks, and Bayesian Classification etc.
Published in Chapter: Crow-ENN: An Optimized Elman Neural Network with Crow Search Algorithm for Leukemia DNA Sequence Classification; From: Mobile Devices and Smart Gadgets in Medical Sciences
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Chapter 13
Information Science in the Analytics of Healthcare Data
Categorization of data and assigns labels or classes to the items in a collection.
Published in Chapter: Information Science in the Analytics of Healthcare Data; From: Integrating AI in IoT Analytics on the Cloud for Healthcare Applications
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Chapter 7
Fuzzy Logic in Health Services: Integrated Fuzzy Method for Multi-Criteria Inventory Classification
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Chapter 167
Data Mining and the KDD Process
Inductive task where a predictive model is learnt from objects labeled with a class and whereby it is possible to predict the class of new objects.
Published in Chapter: Data Mining and the KDD Process; From: Encyclopedia of Information Science and Technology, Fourth Edition
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Chapter 25
Parallel Development of Three Major Space Technology Systems and Human Side of Information Reference Services as an Essential Complementary Method
The process of classification identified and assigned each pixel of all channels of the multi-spectral images to a particular class or theme based on the statistical characteristics of the pixel brightness values known as spectral signatures.
Published in Chapter: Parallel Development of Three Major Space Technology Systems and Human Side of Information Reference Services as an Essential Complementary Method; From: Advanced Methodologies and Technologies in Engineering and Environmental Science
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Chapter 2
Quality and Effectiveness of ERP Software: Data Mining Perspective
A data mining category of data mining challenges that seek to group data into already known sets (classes); hence, the training of the algorithms is considered to have been supervised before the actual task is executed.
Published in Chapter: Quality and Effectiveness of ERP Software: Data Mining Perspective; From: Metrics and Models for Evaluating the Quality and Effectiveness of ERP Software
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Chapter 8
Using Sentiment Analytics to Understand Learner Experiences in Serious Games
A process of categorized the item in a dataset into predefined labels (such as positive and negative).
Published in Chapter: Using Sentiment Analytics to Understand Learner Experiences in Serious Games; From: Next-Generation Applications and Implementations of Gamification Systems
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Chapter 174
Knowledge Discovery in Databases and Data Mining
Data mining task in which the goal is to build a model that assigns class labels to previously unseen and unlabeled examples.
Published in Chapter: Knowledge Discovery in Databases and Data Mining; From: Encyclopedia of Information Science and Technology, Third Edition
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Chapter 16
A Comprehensive Review of Nature-Inspired Algorithms for Feature Selection
Objects that are indiscernible based on their attribute values are belongs to same class and we call it as classification.
Published in Chapter: A Comprehensive Review of Nature-Inspired Algorithms for Feature Selection; From: Handbook of Research on Modeling, Analysis, and Application of Nature-Inspired Metaheuristic Algorithms
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Chapter 11
Patient Data De-Identification: A Conditional Random-Field-Based Supervised Approach
Classification in the machine learning is defined as the supervised learning technique where problem is to identify the class of the new observation with the already developed observations through the labeled data.
Published in Chapter: Patient Data De-Identification: A Conditional Random-Field-Based Supervised Approach; From: Handbook of Research on Applied Cybernetics and Systems Science
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Chapter 7
Machine Learning Techniques for IoT-Based Indoor Tracking and Localization
The most known and commonly used supervised learning method is classification. This method categorizes new unlabeled samples into predefined classes.
Published in Chapter: Machine Learning Techniques for IoT-Based Indoor Tracking and Localization; From: Emerging Trends in IoT and Integration with Data Science, Cloud Computing, and Big Data Analytics
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Chapter 8
Interval Type II Fuzzy Number Generation From Data Set Applied to Sedation Stage Classification
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Chapter 8
Heart Disease Diagnosis: A Machine Learning Approach
It is task of classifying the data into predefined number of classes. It is a supervised approach. The tagged data is used to create classification model that will be used for classification on unknown data.
Published in Chapter: Heart Disease Diagnosis: A Machine Learning Approach; From: Advanced Classification Techniques for Healthcare Analysis
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Chapter 17
Predicting Human Actions Using a Hybrid of ReliefF Feature Selection and Kernel-Based Extreme Learning Machine
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Chapter 6
Minimax Probability Machine: A New Tool for Modeling Seismic Liquefaction Data
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Chapter 24
Default Probability Prediction of Credit Applicants Using a New Fuzzy KNN Method with Optimal Weights
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Chapter 15
Non-Manual Control Devices: Direct Brain-Computer Interaction
Assignment of labels to input patterns based on their extracted features.
Published in Chapter: Non-Manual Control Devices: Direct Brain-Computer Interaction; From: Handbook of Research on Personal Autonomy Technologies and Disability Informatics
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Chapter 43
Composite Classifiers for Bankruptcy Prediction
Form of data analysis that models the relationships between a number of variables and a target feature. The target feature contains nominal values that indicate the class to which each observation belongs.
Published in Chapter: Composite Classifiers for Bankruptcy Prediction; From: Encyclopedia of Business Analytics and Optimization
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Chapter 11
Lesson Engagement and Outlier Extraction Analytics Through Learning Log Classification
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Chapter 3
Analyzing Big Data Using Recent Machine Learning Techniques to Assist Consumers in Online Purchase Decision
Categorizing the given data after successful training. In this process class labels are anticipated and model is developed based on predictive approach.
Published in Chapter: Analyzing Big Data Using Recent Machine Learning Techniques to Assist Consumers in Online Purchase Decision; From: Social Media and Online Consumer Decision Making in the Fashion Industry
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Chapter 51
Methods and Techniques of Data Mining
Inductive task where a predictive model is learnt from objects labeled with a class and whereby it is possible to predict the class of new objects.
Published in Chapter: Methods and Techniques of Data Mining; From: Encyclopedia of Information Science and Technology, Fifth Edition
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Chapter 12
Machine Learning and Its Application in Monitoring Diabetes Mellitus
Classification is the scientific procedure for predicting the class label or category of given test data objects. Classification is also a task of predictive modelling in which a mapping function is approximated using inputted feature variables to produce output target variable.
Published in Chapter: Machine Learning and Its Application in Monitoring Diabetes Mellitus; From: Handbook of Research on Engineering, Business, and Healthcare Applications of Data Science and Analytics
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Chapter 11
Audio-Visual Speech Emotion Recognition
A compact clustering and description of a given instance according to common traits, behaviours and structural features.
Published in Chapter: Audio-Visual Speech Emotion Recognition; From: Encyclopedia of Information Science and Technology, Third Edition
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Chapter 397
An Experimental Sensitivity Analysis of Gaussian and Non-Gaussian Based Methods for Dynamic Modeling in EEG Signal Processing
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Chapter 3
The Effects of Labor Markets and Trade Openness on Economic Growth: A Panel Data Analysis for G-20 C
The systematic arrangement of entities in any field into categories classes based on common characteristics such as properties, morphology, subject matter, etc.
Published in Chapter: The Effects of Labor Markets and Trade Openness on Economic Growth: A Panel Data Analysis for G-20 C; From: Reskilling the Workforce in the Labor Market: The Country Cases
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Chapter 11
Face Recognition in Unconstrained Environment
Classification refers to as assigning a physical object or incident into one of a set of predefined categories.
Published in Chapter: Face Recognition in Unconstrained Environment; From: Handbook of Research on Emerging Perspectives in Intelligent Pattern Recognition, Analysis, and Image Processing
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Chapter 7
Deep Learning Applied to COVID-19 Detection in X-Ray Images
In the context of Deep Learning applications, a classification task consists of assigning a label to each sample of the input data based on the learned features and relationships. In this chapter, the classification task consists of assigning a Chest X-Ray image the label “Positive for COVID-19” or “Negative for COVID-19”.
Published in Chapter: Deep Learning Applied to COVID-19 Detection in X-Ray Images; From: AI Applications for Disease Diagnosis and Treatment
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Chapter 73
Efficient High Dimensional Data Classification
It is a process of predicting the class label of an object for which the class label is unknown; typically a model is built using labeled samples which distinguishes objects of different classes.
Published in Chapter: Efficient High Dimensional Data Classification; From: Encyclopedia of Business Analytics and Optimization
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Chapter 3
Medical Image Classification
A supervised learning process used to predict the class label of a data instance. Training set is used to generate a model and it can be used to predict the class label of test data. An efficient model would be used to classify the new data.
Published in Chapter: Medical Image Classification; From: Medical Image Processing for Improved Clinical Diagnosis
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Chapter 7
Predictive Healthcare Web Analytics Using Machine Learning
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Chapter 7
Application of Deep Learning for EEG
Classification is a process related to categorization, the process in which ideas and objects are recognized, differentiated and understood.
Published in Chapter: Application of Deep Learning for EEG; From: Handbook of Research on Advancements of Artificial Intelligence in Healthcare Engineering
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Chapter 59
Data Mining Tools: Association Rules
Assignment of data into one or more predefined classes.
Published in Chapter: Data Mining Tools: Association Rules; From: Encyclopedia of Business Analytics and Optimization
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Chapter 159
Learning From Imbalanced Data
It is a process by which an unseen sample is assigned a class label by a model trained on data of known class labels.
Published in Chapter: Learning From Imbalanced Data; From: Encyclopedia of Information Science and Technology, Fourth Edition
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Chapter 8
Development, Monitoring, and Management Approaches of Machine Learning Implementations for the Effective Delivery of Government Services
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Chapter 17
Automatic Target Recognition from Inverse Synthetic Aperture Radar Images
The process of dividing objects into different groups or classes using machine learning and artificial intelligence techniques based on their features (attributes).
Published in Chapter: Automatic Target Recognition from Inverse Synthetic Aperture Radar Images; From: Handbook of Research on Advanced Trends in Microwave and Communication Engineering
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Chapter 13
Ideating a Recommender System for Business Growth Using Profit Pattern Mining and Uncertainty Theory
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Chapter 331
Healthcare Informatics
The organization of related objects according to the shared characteristics of interest.
Published in Chapter: Healthcare Informatics; From: Encyclopedia of Information Science and Technology, Third Edition
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Chapter 10
Trends in Distance Education: Theories and Methods
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Chapter 3
Recommendation of Crop and Yield Prediction by Assessing Soil Health From Ortho-Photos
Categorization of objects into groups based on the existing ground truth values. Artificial Intelligence based algorithms classify objects easily.
Published in Chapter: Recommendation of Crop and Yield Prediction by Assessing Soil Health From Ortho-Photos; From: Unmanned Aerial Vehicles and Multidisciplinary Applications Using AI Techniques
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Chapter 303
Parallel Development of Three Major Space Technology Systems and Human Side of Information Reference Services as an Essential Complementary Method
The process of classification identified and assigned each pixel of all channels of the multi-spectral images to a particular class or theme based on the statistical characteristics of the pixel brightness values known as spectral signatures.
Published in Chapter: Parallel Development of Three Major Space Technology Systems and Human Side of Information Reference Services as an Essential Complementary Method; From: Encyclopedia of Information Science and Technology, Fourth Edition
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Chapter 6
Techniques and Methods That Help to Make Big Data the Simplest Recipe for Success
In machine learning and statistics, classification is the problem of identifying to which of a set of categories (sub-populations) a new observation belongs, on the basis of a training set of data containing observations (or instances) whose category membership is known.
Published in Chapter: Techniques and Methods That Help to Make Big Data the Simplest Recipe for Success; From: Big Data Analytics for Entrepreneurial Success
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Chapter 5
Analysis of Gravitation-Based Optimization Algorithms for Clustering and Classification
Classification is the process of categorizing the data into groups based on mathematical information. It is a pattern recognition technique (i.e., finding the meaningful informational patterns from the outlier and noisy data).
Published in Chapter: Analysis of Gravitation-Based Optimization Algorithms for Clustering and Classification; From: Handbook of Research on Big Data Clustering and Machine Learning
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Chapter 13
New Features Extracted From Renal Stone NCCT Images to Predict Retreatment After Shock Wave Lithotripsy (SWL)
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Chapter 6
Subjective and Objective Assessment for Variation of Plant Nitrogen Content to Air Pollutants Using Machine Intelligence: Subjective and Objective Assessment
Classification is a process related to categorization, the process in which ideas and objects are recognized, differentiated, and understood.
Published in Chapter: Subjective and Objective Assessment for Variation of Plant Nitrogen Content to Air Pollutants Using Machine Intelligence: Subjective and Objective Assessment; From: Fuzzy Expert Systems and Applications in Agricultural Diagnosis
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Chapter 23
Learning from Unbalanced Stream Data in Non-Stationary Environments Using Logistic Regression Model: A Novel Approach Using Machine Learning for Assessment of Credit Card Frauds
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Chapter 3
Swarm Intelligence in Solving Bio-Inspired Computing Problems: Reviews, Perspectives, and Challenges
Objects that are indiscernible based on their attribute values are belongs to same class and we call it as classification.
Published in Chapter: Swarm Intelligence in Solving Bio-Inspired Computing Problems: Reviews, Perspectives, and Challenges; From: Handbook of Research on Swarm Intelligence in Engineering
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Chapter 14
Analytics of User Behaviors on Twitter Using Machine Learning
A type of supervised learning algorithm in which algorithm predicts the output as discrete class labels.
Published in Chapter: Analytics of User Behaviors on Twitter Using Machine Learning; From: Handbook of Research on Artificial Intelligence Applications in Literary Works and Social Media
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Chapter 33
Text Classification: New Fuzzy Decision Tree Model
A process to classify objects in classes or categories. These classes are predefined in advance by the user, or it is the system which itself generates these categories.
Published in Chapter: Text Classification: New Fuzzy Decision Tree Model; From: Handbook of Research on Machine Learning Innovations and Trends
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Chapter 11
Search Space Reduction in Biometric Databases: A Review
A technique that logically partitions the database into a small number of predefined classes.
Published in Chapter: Search Space Reduction in Biometric Databases: A Review; From: Developing Next-Generation Countermeasures for Homeland Security Threat Prevention
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Chapter 21
Flexible Classification Standards for Product Data Exchange
A set of concepts, basically classes, properties and relationships between them, with the purpose to allow the linkage of products to product groups (classes) and to describe products in exchange processes between different business partners by commonly defined properties.
Published in Chapter: Flexible Classification Standards for Product Data Exchange; From: Handbook of Research on E-Business Standards and Protocols: Documents, Data and Advanced Web Technologies
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Chapter 4
A Modified Stacking Ensemble Machine Learning Algorithm Using Genetic Algorithms
Classification is the problem of identifying to which of a set of categories a new observation belongs.
Published in Chapter: A Modified Stacking Ensemble Machine Learning Algorithm Using Genetic Algorithms; From: Handbook of Research on Organizational Transformations through Big Data Analytics
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Chapter 19
A Case-Based-Reasoning System for Feature Selection and Diagnosing Asthma
Classification is a general process related to categorization, the process in which ideas and objects are recognized, differentiated, and understood.
Published in Chapter: A Case-Based-Reasoning System for Feature Selection and Diagnosing Asthma; From: Handbook of Research on Data Science for Effective Healthcare Practice and Administration
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Chapter 1
A Review of Soft Computing Methods Application in Rock Mechanic Engineering
Classification system can categorize objects or events using all relevant factors. This system simplify communication of information and guide detailed investigation.
Published in Chapter: A Review of Soft Computing Methods Application in Rock Mechanic Engineering; From: Handbook of Research on Advanced Computational Techniques for Simulation-Based Engineering
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Chapter 13
Plant Disease Classification Using Deep Learning Techniques
An algorithm is trained to predict a category or class for new input data based on patterns it learned from labeled examples. The algorithm tries to categorize new data into pre-defined groups or classes.
Published in Chapter: Plant Disease Classification Using Deep Learning Techniques; From: Effective AI, Blockchain, and E-Governance Applications for Knowledge Discovery and Management
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