TITLE

Receiver Operating Characteristic (ROC) Curves for Measuring the Quality of Decisions in Cricket

PUB. DATE
April 2010
SOURCE
Journal of Quantitative Analysis in Sports;Apr2010, Vol. 6 Issue 2, p1246
SOURCE TYPE
Academic Journal
DOC. TYPE
Article
ABSTRACT
No abstract available.
ACCESSION #
50509713

 

Related Articles

  • PRROC: computing and visualizing precision-recall and receiver operating characteristic curves in R. Grau, Jan; Grosse, Ivo; Keilwagen, Jens // Bioinformatics;8/1/2015, Vol. 31 Issue 15, p2595 

    Precision-recall (PR) and receiver operating characteristic (ROC) curves are valuable measures of classifier performance. Here, we present the R-package PRROC, which allows for computing and visualizing both PR and ROC curves. In contrast to available R-packages, PRROC allows for computing PR...

  • The area under the ROC curve: Is it a valid measure of screening performance? Wald, Nicholas J; Bestwick, Jonathan P // Journal of Medical Screening;Dec2014, Vol. 21 Issue 4, p220 

    A letter to the editor is presented related to the assessment of the validity of area under the curve (AUC), a curve used to measure the performance of screening and which fall under the receiver operating characteristic (ROC).

  • 2. The ROC Decision Model.  // Journal of the ICRU;Jun2008, Vol. 8 Issue 1, p19 

    The article identifies the factors to consider in designing statistical decision models. The receiver operating characteristics (ROC) model need specific factors to ensure its reliability in presenting good outcomes during experiments. The ROC analysis comes in different model which include the...

  • Use of outcomes to evaluate surveillance systems for bioterrorist attacks. McBrien, Kerry A.; Kleinman, Ken P.; Abrams, Allyson M.; Prosser, Lisa A. // BMC Medical Informatics & Decision Making;2010, Vol. 10 Issue 1, p25 

    Background: Syndromic surveillance systems can potentially be used to detect a bioterrorist attack earlier than traditional surveillance, by virtue of their near real-time analysis of relevant data. Receiver operator characteristic (ROC) curve analysis using the area under the curve (AUC) as a...

  • Designing a Rational Screening Program. Miller, Joseph M. // American Orthoptic Journal;2006, Vol. 56, p30 

    Introduction: The design of a rational screening program is predicated upon reliable rates of referral with know sensitivity and specificity for a given referral threshold. Such decision making is facilitated through the use of Receiver Operator Characteristic (ROC) curves. Methods: The...

  • Using ROC curves to test models of recognition memory: The relationship between presentation... Hirshman, Elliot; Hostetter, Mark // Memory & Cognition;Mar2000, Vol. 28 Issue 2, p161 

    Examines the relationship between presentation duration and slope using receiver-operating characteristics (ROC) curves to test models of recognition memory. Reduction of the slope of the z-transformed ROC curve with increasing presentation duration; Changes in the z-transformed ROC curve...

  • Quantitative Assessment of Risks Considering Threshold Effects of Object- Oriented Metrics Using Open Source Software. MALHOTRA, RUCHIKA; BANSAL, ANKITA JAIN // Software Quality Professional;Sep2012, Vol. 14 Issue 4, p33 

    The empirical validation of software metrics to predict software quality is very important in the field of research. There are a number of empirical studies that identify the relationship between software quality and object-oriented metrics. One of the attributes used to measure software quality...

  • Small-sample precision of ROC-related estimates. Hanczar, Blaise; Jianping Hua; Chao Sima; Weinstein, John; Bittner, Michael; Dougherty, Edward R. // Bioinformatics;Mar2010, Vol. 26 Issue 6, p822 

    Motivation: The receiver operator characteristic (ROC) curves are commonly used in biomedical applications to judge the performance of a discriminant across varying decision thresholds. The estimated ROC curve depends on the true positive rate (TPR) and false positive rate (FPR), with the key...

  • The ROC Curve and the Area under It as Performance Measures. Marzban, Caren // Weather & Forecasting;Dec2004, Vol. 19 Issue 6, p1106 

    The receiver operating characteristic (ROC) curve is a two-dimensional measure of classification performance. The area under the ROC curve (AUC) is a scalar measure gauging one facet of performance. In this short article, five idealized models are utilized to relate the shape of the ROC curve,...

  • CLASSIFIER ENSEMBLES WITH ASYMMETRIC MISCLASSIFICATION COSTS IN MEDICAL DIAGNOSIS. Novakovic, Jasmina; Veljovic, Alempije // Metalurgia International;Jan2012, Vol. 17 Issue 1, p114 

    In this research, cost-sensitive classifier ensembles that can incorporate unequal misclassification into classifier ensembles models for medical diagnosis are suggested. We chose classifier ensembles with decision trees, as the base classifiers because they are sensitive to rotation of the...

Share

Read the Article

Courtesy of THE LIBRARY OF VIRGINIA

Sorry, but this item is not currently available from your library.

Try another library?
Sign out of this library

Other Topics