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 Cross-Validation

Chapter 20
Handbook of Research on Innovations and Applications of AI, IoT, and Cognitive Technologies
It provides information about how well a classifier generalizes and is generally used to evaluate machine learning models on a limited data sample.
Published in Chapter:
Traditional and Innovative Approaches for Detecting Hazardous Liquids
Ebru Efeoglu (Istanbul Gedik University, Turkey) and Gurkan Tuna (Trakya University, Turkey)
Copyright: © 2021 |Pages: 20
DOI: 10.4018/978-1-7998-6870-5.ch020
Abstract
In this chapter, traditional and innovative approaches used in hazardous liquid detection are reviewed, and a novel approach for the detection of hazardous liquids is presented. The proposed system is based on electromagnetic response measurements of liquids in the microwave frequency band. Thanks to this technique, liquid classification can be made quickly without pouring the liquid from its bottle and without opening the lid of its bottle. The system can detect solutions with hazardous liquid concentrations of 70% or more, as well as pure hazardous liquids. Since it relies on machine learning methods and the success of all machine learning methods depends on provided data type and dataset, a performance evaluation study has been carried out to find the most suitable method. In the performance evaluation study naive Bayes and sequential minimal optimization has been evaluated, and the results have shown that naive Bayes is more suitable for liquid classification.
Full Text Chapter Download: US $37.50 Add to Cart
More Results
Chapter 2
Predictive Modelling for Financial Fraud Detection Using Data Analytics: A Gradient-Boosting Decision Tree
A re-sampling technique that uses diverse percentages of a dataset to train and test the model of improved iterations.
Published in Chapter: Predictive Modelling for Financial Fraud Detection Using Data Analytics: A Gradient-Boosting Decision Tree; From: Applications of Machine Learning and Deep Learning for Privacy and Cybersecurity
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 11
Applying Machine Learning Methods for Credit Card Payment Default Prediction With Cost Savings
This is a region formed out of the Training dataset with the primary objective of hyperparameter tuning the machine learning models to achieve the best performance. This entire process of hyperparameter tuning using a cross-validation region is called a cross-validation process.
Published in Chapter: Applying Machine Learning Methods for Credit Card Payment Default Prediction With Cost Savings; From: Biomedical and Business Applications Using Artificial Neural Networks and Machine Learning
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 28
Secure Routing with Reputation in MANET
A statistical method derived from cross-classification which main objective is to detect the outlying point in a population set. It is a candidate method for anomalies detection in the reputation sharing (recommendations) and regular communication in MANET. Denial-of-Service (DoS) attack: An attempt of keeping an access to computer resources (nodes) unavailable, especially by generating dummy traffic from one source (DoS) or a large number of sources (distributed DoS [DDoS]).
Published in Chapter: Secure Routing with Reputation in MANET; From: Handbook of Research on Wireless Security
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 48
Automated Essay Scoring Systems
Validating a scoring procedure (here, for essays) by applying it to another set of data.
Published in Chapter: Automated Essay Scoring Systems; From: Handbook of Research on New Media Literacy at the K-12 Level: Issues and Challenges
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 186
Employee Classification in Reward Allocation Using ML Algorithms
A statistical technique used in machine learning to overcome the Overfitting problem. The full data set is partitioned into ‘training data’ and ‘validation and testing data’ by creating multiple manyfold samples using random sampling with replacement. The number of folds determines the number of times the full data set is shuffled and partitioned, and that many models are built to determine the pattern of .
Published in Chapter: Employee Classification in Reward Allocation Using ML Algorithms; From: Encyclopedia of Data Science and Machine Learning
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 10
Privacy Preservation of Image Data With Machine Learning
A check approaches evaluating the capacity of a system to generalize an independent dataset. It provides a database used to evaluate the learned model for fitting throughout the training phase. The effectiveness of individual prediction functions may also be evaluated via cross-validation. The training samples will be randomly divided into k mutually exclusive sub-samples of fixed size in k-fold cross-validation. The model is trained k times, in which one of the k subsamples is used for each iteration, while the other k-1 subsamples are employed to exercise the system. Cross-validation findings are combined to assess the exactness as a single estimate.
Published in Chapter: Privacy Preservation of Image Data With Machine Learning; From: Applications of Machine Learning and Deep Learning for Privacy and Cybersecurity
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 6
Machine Learning Approach for Kashmiri Word Sense Disambiguation
Cross-validation is a valuable technique that gives a reliable estimate of the performance of the machine learning model. It is helpful in spotting the overfitting issues as well as deciding the relevant parameters and best model for the task at hand.
Published in Chapter: Machine Learning Approach for Kashmiri Word Sense Disambiguation; From: Empowering Low-Resource Languages With NLP Solutions
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 5
AI-Empowered 6G and Next Generation Networks
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 1
A Machine Learning Approach to Classify the Telecommunication Customers Based on Their Profitability
Cross-validation is a resampling method for evaluating machine learning models on a small sample of data.
Published in Chapter: A Machine Learning Approach to Classify the Telecommunication Customers Based on Their Profitability; From: Social Customer Relationship Management (Social-CRM) in the Era of Web 4.0
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 79
EA Multi-Model Selection for SVM
A method of estimating predictive error of inducers. Cross-validation procedure splits that dataset into k equal-sized pieces called folds. k predictive function are built, each tested on a distinct fold after being trained on the remaining folds.
Published in Chapter: EA Multi-Model Selection for SVM; From: Encyclopedia of Artificial Intelligence
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 2
Web Development Effort Estimation: An Empirical Analysis
Process by which an original dataset d is divided into a training set t and a validation set v. The training set is used to produce an effort estimation model (if applicable), later used to predict effort for each of the projects in v, as if these projects were new projects for which effort was unknown. Accuracy statistics are then obtained and aggregated to provide an overall measure of prediction accuracy.
Published in Chapter: Web Development Effort Estimation: An Empirical Analysis; From: Handbook of Research on Web Information Systems Quality
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 10
Approach to Minimize Bias on Aesthetic Image Datasets
A model validation technique for assessing how the results of a statistical analysis will generalize to an independent data set.
Published in Chapter: Approach to Minimize Bias on Aesthetic Image Datasets; From: Interface Support for Creativity, Productivity, and Expression in Computer Graphics
Full Text Chapter Download: US $37.50 Add to Cart
eContent Pro Discount Banner
InfoSci OnDemandECP Editorial ServicesAGOSR