Insights into the area under the receiver operating characteristic curve (AUC) as a discrimination measure in species distribution modelling
نویسندگان
چکیده
منابع مشابه
part 5: receiver operating characteristic curve and area under the curve
multiple diagnostic tools are used by emergency physicians, every day. in addition, new tools are evaluated to obtain more accurate methods and reduce time or cost of conventional ones. in the previous parts of this educational series, we described diagnostic performance characteristics of diagnostic tests including sensitivity, specificity, positive and negative predictive values, and likeliho...
متن کاملThe meaning and use of the area under a receiver operating characteristic (ROC) curve.
A representation and interpretation of the area under a receiver operating characteristic (ROC) curve obtained by the "rating" method, or by mathematical predictions based on patient characteristics, is presented. It is shown that in such a setting the area represents the probability that a randomly chosen diseased subject is (correctly) rated or ranked with greater suspicion than a randomly ch...
متن کاملConfidence Intervals for the Probability of Superiority Effect Size Measure and the Area Under a Receiver Operating Characteristic Curve.
It is good scientific practice to the report an appropriate estimate of effect size and a confidence interval (CI) to indicate the precision with which a population effect was estimated. For comparisons of 2 independent groups, a probability-based effect size estimator (A) that is equal to the area under a receiver operating characteristic curve and closely related to the popular Wilcoxon-Mann-...
متن کاملEstimating the Area under a Receiver Operating Characteristic (ROC) Curve For Repeated Measures Design
The receiver operating characteristic (ROC) curve is widely used for diagnosing as well as for judging the discrimination ability of different statistical models. Although theories about ROC curves have been established and computation methods and computer software are available for cross-sectional design, limited research for estimating ROC curves and their summary statistics has been done for...
متن کاملA Discretization Method Based on Maximizing the Area under Receiver Operating Characteristic Curve
Many machine learning algorithms require the features to be categorical. Hence, they require all numeric-valued data to be discretized into intervals. In this paper, we present a new discretization method based on the receiver operating characteristics (ROC) Curve (AUC) measure. Maximum area under ROC curve-based discretization (MAD) is a global, static and supervised discretization method. MAD...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Global Ecology and Biogeography
سال: 2011
ISSN: 1466-822X
DOI: 10.1111/j.1466-8238.2011.00683.x