Search the World's Largest Database of Information Science & Technology Terms & Definitions
InfInfoScipedia LogoScipedia
A Free Service of IGI Global Publishing House
Below please find a list of definitions for the term that
you selected from multiple scholarly research resources.

What is ROC Curve

Chapter 1
Analyzing Data Through Probabilistic Modeling in Statistics
Receiver operating characteristic curve is a graph that shows the performance of a classification model at all classification thresholds.
Published in Chapter:
Determination of Poverty Indicators Using Roc Curves in Turkey
Zübeyde Çiçek (Süleyman Demirel University, Turkey) and Hakan Demirgil (Suleyman Demirel University, Turkey)
Copyright: © 2021 |Pages: 24
DOI: 10.4018/978-1-7998-4706-9.ch001
Abstract
The present study was conducted to determine the reasons affecting poverty in Turkey and specify the level of significance of these reasons to explain poverty. The data which was analyzed in the study were retrieved from the Household Budget Research which was published by the Turkish Statistical Institute. In the study, logit models have been established by taking into account the demographic and socioeconomic indicators and the characteristics of the household. For each of these models, ROC curves were drawn, and the best model was found with the help of the areas under the curve. The results showed that the model which was developed based on the variables related to housing and the model according to consumption expenditure were determined to be more significant to explain poverty. Also, the rental value of the house, the floor type of the house and household's head educational level were found to be the most significant determinants of poverty according to the analysis of the results.
Full Text Chapter Download: US $37.50 Add to Cart
More Results
Chapter 57
Using Receiver Operating Characteristic (ROC) Analysis to Evaluate Information-Based Decision-Making
A curve that plots a diagnostic test’s sensitivity versus its false positive rate across all possible threshold values for defining positivity.
Published in Chapter: Using Receiver Operating Characteristic (ROC) Analysis to Evaluate Information-Based Decision-Making; From: Advanced Methodologies and Technologies in Business Operations and Management
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 16
The Clinical Utility of Psychometric Tests: A Real-Data Approach From a Study Including Children With ADHD
A descriptive graph that shows the relationship between sensitivity (TPR) (y-axis) and FPR (1-specificity, x-axis) for every possible cutoff point of a test.
Published in Chapter: The Clinical Utility of Psychometric Tests: A Real-Data Approach From a Study Including Children With ADHD; From: Handbook of Research on Critical Issues in Special Education for School Rehabilitation Practices
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 10
The Influence of Artificial Intelligence on People With Autism Spectrum Disorder: A Methodical Literature Review
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 192
Using Receiver Operating Characteristic (ROC) Analysis to Evaluate Information -Based Decision-Making
A curve that plots a diagnostic test’s sensitivity versus its false positive rate across all possible threshold values for defining positivity.
Published in Chapter: Using Receiver Operating Characteristic (ROC) Analysis to Evaluate Information -Based Decision-Making; From: Encyclopedia of Information Science and Technology, Fourth Edition
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 189
ROC Analysis in Business Decision-makings
a curve that plots a diagnostic test’s sensitivity versus its false positive rate across all possible threshold values for defining positivity.
Published in Chapter: ROC Analysis in Business Decision-makings; From: Encyclopedia of Business Analytics and Optimization
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 22
Decision Fusion of Multisensor Images for Human Face Identification in Information Security
Receiver Operating Characteristics (ROC) curve is especially useful in pattern recognition problem for evaluating the performance of the classifier in terms of false positive rate and true positive rate.
Published in Chapter: Decision Fusion of Multisensor Images for Human Face Identification in Information Security; From: Handbook of Research on Computational Intelligence for Engineering, Science, and Business
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 4
On the Evaluation of Early Warning Models for Financial Crises
The acronym stands for Receiver Operating Characteristic curve. It illustrates the performance of an EWM by plotting the true positive rate against the false positive rate associated with various warning thresholds.
Published in Chapter: On the Evaluation of Early Warning Models for Financial Crises; From: Handbook of Research on Financial and Banking Crisis Prediction through Early Warning Systems
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 9
Digital Recognition of Breast Cancer Using TakhisisNet: An Innovative Multi-Head Convolutional Neural Network for Classifying Breast Ultrasonic Images
A receiver operating characteristic (ROC) curve is a graph showing the performance of a classification model at all classification thresholds. This curve plots two parameters: True Positive Rate vs. False Positive Rate.
Published in Chapter: Digital Recognition of Breast Cancer Using TakhisisNet: An Innovative Multi-Head Convolutional Neural Network for Classifying Breast Ultrasonic Images; From: Opportunities and Challenges in Digital Healthcare Innovation
Full Text Chapter Download: US $37.50 Add to Cart
eContent Pro Discount Banner
InfoSci OnDemandECP Editorial ServicesAGOSR