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What is Logistic Regression

Chapter 9
Handbook of Research on Credential Innovations for Inclusive Pathways to Professions
A logistic regression is a type of statistical model typically using a logistic function to see what predicts a categorical dependent variable. In this case the categories are a) the certification has a military designation or b) it does not have the designation.
Published in Chapter:
Military-to-Civilian Transition Through Credentials: Certification Promotion by Military COOL Program
Mary Tschirhart (The George Washington University, USA) and Huang Chen (The George Washington University, USA)
Copyright: © 2022 |Pages: 16
DOI: 10.4018/978-1-7998-3820-3.ch009
Abstract
This chapter reviews the United States COOL programs' promotion of certification during military employment to support transition to civilian employment and the CareerOneStop platform which profiles certifications. Some certifications on CareerOneStop have a designation from COOL indicating relevance to military workers. The chapter presents analyses showing that certain types of certifications are more likely to have a military designation than others. In brief, the designation is more likely for accredited and industry-recognized certifications and those tied to occupations with lower annual median wages and predictions of decrease and increase in employment versus a more stable trajectory. Some occupations also significantly differ in the likelihood of a military designation for certifications tied to it. The authors close with a discussion of recommendations including additional questions for consideration.
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Chapter 25
Characteristics of Farm and Rural Internet Use in the USA
A regression model where the dependent variable takes on a limited number of discrete values, often two values representing yes and no.
Published in Chapter: Characteristics of Farm and Rural Internet Use in the USA; From: Handbook of Research on Global Diffusion of Broadband Data Transmission
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Chapter 21
Visualization of Predictive Modeling for Big Data Using Various Approaches When There Are Rare Events at Differing Levels
A regression model that is used when the dependent variable is qualitative and a probability is assigned to an observation for the likelihood that the target variable has a value of 1.
Published in Chapter: Visualization of Predictive Modeling for Big Data Using Various Approaches When There Are Rare Events at Differing Levels; From: Handbook of Research on Big Data Storage and Visualization Techniques
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Chapter 19
Crime Hotspot Prediction Using Big Data in China
Logistic regression analysis is mainly used in epidemiology. The most common case is to explore the risk factors of a certain disease and predict the probability of the occurrence of a certain disease according to the risk factors.
Published in Chapter: Crime Hotspot Prediction Using Big Data in China; From: Handbook of Research on Managerial Practices and Disruptive Innovation in Asia
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Chapter 13
Application of Machine Learning In Forensic Science
Logistic regression is used when the response variable is categorical in nature.
Published in Chapter: Application of Machine Learning In Forensic Science; From: Critical Concepts, Standards, and Techniques in Cyber Forensics
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Chapter 13
A Comprehensive Review on AI Techniques for Healthcare
It is an algorithm used in the software to understand the relation between dependent and independent variables by estimating probabilities using logistic regression equation. This algorithm helps you to predict the likeliness on an event happening.
Published in Chapter: A Comprehensive Review on AI Techniques for Healthcare; From: Revolutionizing Healthcare Through Artificial Intelligence and Internet of Things Applications
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Chapter 9
Ethnicity and Household Savings in Indonesia
the appropriate regression analysis to conduct when the dependent variable is dichotomous (binary).
Published in Chapter: Ethnicity and Household Savings in Indonesia; From: Economics, Business, and Islamic Finance in ASEAN Economics Community
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Chapter 7
Methodology for Transformation of Behavioural Cues into Social Signals in Human-Computer Interaction
Logistic regression is a type of regression analysis used for predicting the outcome of categorical dependent variable based on one or more predictor variables.
Published in Chapter: Methodology for Transformation of Behavioural Cues into Social Signals in Human-Computer Interaction; From: Handbook of Research on Interactive Information Quality in Expanding Social Network Communications
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Chapter 17
Mobile DM Coupon Promotion in Japan: A Case Study on Response Behavior Changes in Services Consumption
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Chapter 18
Student Collaborative Learning Strategies: A Logistic Regression Analysis Approach
This is a kind of regression analysis often used when the outcome variable is dichotomous and scored 0, 1. Logistic regression is also known as logit regression and when the dependent variable has more than two categories it is called multinomial. Logistic regression is used when predicting whether an event will happen or not.
Published in Chapter: Student Collaborative Learning Strategies: A Logistic Regression Analysis Approach; From: Handbook of Research on Innovations in Non-Traditional Educational Practices
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Chapter 18
Skin Cancer Lesion Detection Using Improved CNN Techniques
is used to quantify the predictability, and then the classifier is employed. For example, it can anticipate or provide a true or false result. Researchers in determined to engage this classifier.
Published in Chapter: Skin Cancer Lesion Detection Using Improved CNN Techniques; From: Handbook of Research on Technological Advances of Library and Information Science in Industry 5.0
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Chapter 55
Initial Stages to Create Online Graduate Communities: Assessment and Development
Logistic regression is a method of statistical modeling appropriate for categorical outcome variables. It describes the relationship between a categorical response variable and a set of explanatory variables.
Published in Chapter: Initial Stages to Create Online Graduate Communities: Assessment and Development; From: Encyclopedia of Information Communication Technologies and Adult Education Integration
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Chapter 30
Clinical Decision Making by Emergency Room Physicians and Residents
Technique for making predictions when a dependent variable is a categorical dichotomy, and the independent variable(s) are continuous and/or categorical.
Published in Chapter: Clinical Decision Making by Emergency Room Physicians and Residents; From: Encyclopedia of Healthcare Information Systems
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Chapter 166
Multilogistic Regression by Product Units
Statistical regression model for Bernoulli-distributed dependent variables. It is a generalized linear model that uses the logit as its link function. Logistic regression applies maximum likelihood estimation after transforming the dependent into a logit variable (the natural log of the odds of the dependent occurring or not).
Published in Chapter: Multilogistic Regression by Product Units; From: Encyclopedia of Artificial Intelligence
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Chapter 9
Exploring Public Perceptions of COVID-19 Vaccine Adverse Effects Through Social Media Analysis
LR is a classification problem-solving supervised ML technique. With the exception of how they are applied, LR and linear regression are very similar. While LR is used to solve classification problems, linear regression is used to solve regression problems ( Ferawati et al., 2022 ).
Published in Chapter: Exploring Public Perceptions of COVID-19 Vaccine Adverse Effects Through Social Media Analysis; From: Handbook of Research on Advancements of Contactless Technology and Service Innovation in Library and Information Science
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Chapter 9
Genetic Algorithms for Small Enterprises Default Prediction: Empirical Evidence from Italy
Logistic regression is a statistical method for determining the relationship between independent predictor variables (such as financial ratios) and a dichotomously coded dependent variable (such as default or non-default).
Published in Chapter: Genetic Algorithms for Small Enterprises Default Prediction: Empirical Evidence from Italy; From: Handbook of Research on Novel Soft Computing Intelligent Algorithms: Theory and Practical Applications
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Chapter 2
An Exploratory Analysis and Predictive SIR Model for the Early Onset of COVID-19 in Tamil Nadu, India
A regression model built using exponential functions for dichotomous variables; usually non-linear in nature.
Published in Chapter: An Exploratory Analysis and Predictive SIR Model for the Early Onset of COVID-19 in Tamil Nadu, India; From: Machine Learning and Data Analytics for Predicting, Managing, and Monitoring Disease
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Chapter 1
Adoption of Churn Recognition System to Predict Customer Churn: A Study With Respect to Semiconductor Supply Chain
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Chapter 22
An Analysis and Detection of Misleading Information on Social Media Using Machine Learning Techniques
Whenever the quantity is predictable is definite, and then the classifier is employed. For example, it can anticipate or provide a true or false result. Researchers in determine engaged this classifier.
Published in Chapter: An Analysis and Detection of Misleading Information on Social Media Using Machine Learning Techniques; From: Handbook of Research on Cyber Approaches to Public Administration and Social Policy
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Chapter 2
Predictive Analytics
Logistic regression is a predictive analytic method for describing and explaining the relationships between a categorical dependent variable and one or more continuous or categorical independent variables in the recent and past existing data in efforts to build predictive models for predicting a membership of individuals or products into two groups or categories.
Published in Chapter: Predictive Analytics; From: Handbook of Research on Organizational Transformations through Big Data Analytics
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Chapter 8
Machine Learning in Python: Diabetes Prediction Using Machine Learning
Logistic regression is a classification algorithm that comes under supervised learning and is used for predictive learning. Logistic regression is used to describe data. It works best for dichotomous (binary) classification.
Published in Chapter: Machine Learning in Python: Diabetes Prediction Using Machine Learning; From: Handbook of Research on Applications and Implementations of Machine Learning Techniques
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Chapter 55
Data Mining Applications in a Medical System: A Case Study
Logistic regression is a particular type of regression which is used in cases that response variable is double-choice or multiple-choice.
Published in Chapter: Data Mining Applications in a Medical System: A Case Study; From: Encyclopedia of Business Analytics and Optimization
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Chapter 9
Merchants Competing on E-Commerce Platforms: Influencing Factors on Buying Behavior
A logistic regression describes a regression analysis in which the dependent variable is discrete. In the logistic regressions performed in this book chapter, the dependent variable is scaled binary - purchase or non-purchase.
Published in Chapter: Merchants Competing on E-Commerce Platforms: Influencing Factors on Buying Behavior; From: Handbook of Research on the Platform Economy and the Evolution of E-Commerce
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Chapter 17
Comparing Conventional Methods With Fuzzy Logic for Quantifying Road Congestion: Evidence From Central Kolkata, India
Whenever the quantity is predictable, is definite, then the classifier is employed. For example, it can anticipate or provide a true or false result. Researchers in determine engaged this classifier
Published in Chapter: Comparing Conventional Methods With Fuzzy Logic for Quantifying Road Congestion: Evidence From Central Kolkata, India; From: Handbook of Research on Technological Advances of Library and Information Science in Industry 5.0
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