Results 51 to 60 of about 2,524,964 (264)
Comparing ROC Curves Derived From Regression Models [PDF]
, 2011 In constructing predictive models, investigators frequently assess the incremental value of a predictive marker by comparing the ROC curve generated from the predictive model including the new marker with the ROC curve from the model excluding the new ...
Begg, Colin B +2 more
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On optimal reject rules and ROC curves [PDF]
Pattern Recognition Letters, 2005 In this paper we make the connection between two approaches for supervised classification with a rejection option. The first approach is due to Tortorella and is based on ROC curves and the second is a generalisation of Chow's optimal rule.
Pires, Ana M., Santos-Pereira, Carla
openaire +4 more sources
nsROC: An R package for Non-Standard ROC Curve Analysis
The R Journal, 2018 The receiver operating characteristic (ROC) curve is a graphical method which has become standard in the analysis of diagnostic markers, that is, in the study of the classification ability of a numerical variable.
Sonia Pérez-Fernández +3 more
semanticscholar +1 more source
Semi-Parametric Maximum Likelihood Estimates for ROC Curves of Continuous-Scale Tests [PDF]
, 2008 In this paper, we propose a new semi-parametric maximum likelihood (ML) estimate of an ROC curve that satisfies the property of invariance of the ROC curve and is easy to compute.
Lin, Huazhen, Zhou, Xiao-Hua
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Prequential AUC: properties of the area under the ROC curve for data streams with concept drift
Knowledge and Information Systems, 2017 Modern data-driven systems often require classifiers capable of dealing with streaming imbalanced data and concept changes. The assessment of learning algorithms in such scenarios is still a challenge, as existing online evaluation measures focus on ...
D. Brzezinski, J. Stefanowski
semanticscholar +1 more source
BMC Medical Informatics and Decision Making, 2011 Background Decision curve analysis has been introduced as a method to evaluate prediction models in terms of their clinical consequences if used for a binary classification of subjects into a group who should and into a group who should not be treated ...
Zumbrunn Thomas, Rousson Valentin
doaj +1 more source
A boosting method for maximizing the partial area under the ROC curve
BMC Bioinformatics, 2010 Background The receiver operating characteristic (ROC) curve is a fundamental tool to assess the discriminant performance for not only a single marker but also a score function combining multiple markers.
Eguchi Shinto, Komori Osamu
doaj +1 more source
Komparasi Algoritma Multi Layer Perceptron dan Radial Basis Function untuk Diagnosa Penyakit Jantung [PDF]
, 2014 Neural network as a data mining model has many algorithms with different accuracy level. This research use UCI machine learning repository's data to compare the accuracy level of Multilayer Perceptron (MLP) and Radial Basis Function (RBF) algorithm in ...
Setiadi, A. (Ahmad)
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Monitoring Livestock Health by Modeling Rumination Behavior According to Accelerometer-Based Information [PDF]
Journal of Agricultural MachineryIntroductionThe livestock sector excels in the production of dairy and meat products. These products, serving as vital sources of animal protein, hold a significant position in household diets.
E. Vahedi Tekmehdash +4 more
doaj +1 more source
Electronic Journal of Statistics, 2015 In binary classification problems, the area under the ROC curve (AUC) is commonly used to evaluate the performance of a prediction model. Often, it is combined with cross-validation in order to assess how the results will generalize to an independent ...
E. LeDell +2 more
semanticscholar +1 more source