Bivariate ROC Curve

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

ROC Curve

It would be nice for both the woman and family and the attending obstetrician to anticipate a cesarean delivery on the basis of patient characteristics. The traditional method is to compute Bishop score based on dilatation, effacement, consistency and position. Other parameters that influence the success of induction of labor are maternal age, parity, BMI and amniotic fluid index. A study was c...

متن کامل

Bivariate marker measurements and ROC analysis.

This article considers receiver operating characteristic (ROC) analysis for bivariate marker measurements. The research interest is to extend tools and rules from univariate marker to bivariate marker setting for evaluating predictive accuracy of markers using a tree-based classification rule. Using an and-or classifier, an ROC function together with a weighted ROC function (WROC) and their con...

متن کامل

Roc Curve Estimation: an Overview

• This work overviews some developments on the estimation of the Receiver Operating Characteristic (ROC) curve. Estimation methods in this area are constantly being developed, adjusted and extended, and it is thus impossible to cover all topics and areas of application in a single paper. Here, we focus on some frequentist and Bayesian methods which have been mostly employed in the medical setti...

متن کامل

On Bootstrapping the ROC Curve

This paper is devoted to thoroughly investigating how to bootstrap the ROC curve, a widely used visual tool for evaluating the accuracy of test/scoring statistics in the bipartite setup. The issue of confidence bands for the ROC curve is considered and a resampling procedure based on a smooth version of the empirical distribution called the ”smoothed bootstrap” is introduced. Theoretical argume...

متن کامل

Bending the Curve: Improving the ROC Curve Through Error Redistribution

Classification performance is often not uniform over the data. Some areas in the input space are easier to classify than others. Features that hold information about the ”difficulty” of the data may be nondiscriminative and are therefore disregarded in the classification process. We propose a meta-learning approach where performance may be improved by post-processing. This improvement is done b...

متن کامل

ذخیره 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: Communications for Statistical Applications and Methods

سال: 2012

ISSN: 2287-7843

DOI: 10.5351/ckss.2012.19.2.277