Supplemental: Active Diagnosis via AUC Maximization

نویسندگان

  • Gowtham Bellala
  • Jason Stanley
  • Clayton Scott
  • Suresh K. Bhavnani
چکیده

1 AUC Estimation The area under the ROC curve can be approximated using lower rectangles, upper rectangles or by using a linear approximation, as shown in Figure 1. The expressions related to each of these approximations are Al(zA) = M−1 ∑ t=0 (1− M̂Rt)(F̂ARt+1 − F̂ARt) Au(zA) = M−1 ∑ t=0 (1− M̂Rt+1)(F̂ARt+1 − F̂ARt) Am(zA) = M−1 ∑ t=0 (1− M̂Rt + M̂Rt+1 2 )(F̂ARt+1 − F̂ARt). Substituting the estimates for miss rate and false alarm rate, the corresponding approximations for the area above the ROC curve are given by Al(zA) = M ∑ i=1 M ∑ j=i Pr(Xr(i) = 0|zA)Pr(Xr(j) = 1|zA) M ∑ i=1 Pr(Xi = 1|zA) M ∑ i=1 Pr(Xi = 0|zA) (1a)

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

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Active Diagnosis via AUC Maximization: An Efficient Approach for Multiple Fault Identification in Large Scale, Noisy Networks

The problem of active diagnosis arises in several applications such as disease diagnosis, and fault diagnosis in computer networks, where the goal is to rapidly identify the binary states of a set of objects (e.g., faulty or working) by sequentially selecting, and observing, (noisy) responses to binary valued queries. Current algorithms in this area rely on loopy belief propagation for active q...

متن کامل

AUC Maximization with K-hyperplane

The area under the ROC curve (AUC) is a measure of interest in various machine learning and data mining applications. It has been widely used to evaluate classification performance on heavily imbalanced data. The kernelized AUC maximization machines have established a superior generalization ability compared to linear AUC machines because of their capability in modeling the complex nonlinear st...

متن کامل

A study on risk factors and diagnostic efficiency of posthepatectomy liver failure in the nonobstructive jaundice

Liver failure remains as the most common complication and cause of death after hepatectomy, and continues to be a challenge for doctors.t test and χ test were used for single factor analysis of data-related variables, then results were introduced into the model to undergo the multiple factors logistic regression analysis. Pearson correlation analysis was performed for related postoperative inde...

متن کامل

Empirical performance maximization for linear rank statistics

The ROC curve is known to be the golden standard for measuring performance of a test/scoring statistic regarding its capacity of discrimination between two populations in a wide variety of applications, ranging from anomaly detection in signal processing to information retrieval, through medical diagnosis. Most practical performance measures used in scoring applications such as the AUC, the loc...

متن کامل

Stochastic Online AUC Maximization

Area under ROC (AUC) is a metric which is widely used for measuring the classification performance for imbalanced data. It is of theoretical and practical interest to develop online learning algorithms that maximizes AUC for large-scale data. A specific challenge in developing online AUC maximization algorithm is that the learning objective function is usually defined over a pair of training ex...

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

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

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2011