Regression Curve Analysis of Cephalosporin Activity

Tree Induction vs. Logistic Regression: A Learning-Curve Analysis

Tree Induction vs. Logistic Regression: A Learning-Curve Analysis

Tree induction and logistic regression are two standard o the shelf methods for building models for classi cation We present a large scale experimental comparison of logistic regression and tree induction assessing classi cation ac curacy and the quality of rankings based on class membership probabilities We use a learning curve analysis to examine the relationship of these measures to the size...

Regression Analysis for the Partial Area under the Roc Curve

Performance evaluation of any classification method is fundamental to its acceptance in practice. Evaluation should consider the dependence of a classifier’s accuracy on relevant covariates in addition to its overall accuracy. When developing a classifier with a continuous output that allocates units into one of two groups, receiver operating characteristic (ROC) curve analysis is appropriate. ...

ROC curve regression analysis: the use of ordinal regression models for diagnostic test assessment.

Diagnostic tests commonly are characterized by their true positive (sensitivity) and true negative (specificity) classification rates, which rely on a single decision threshold to classify a test result as positive. A more complete description of test accuracy is given by the receiver operating characteristic (ROC) curve, a graph of the false positive and true positive rates obtained as the dec...

Activity of faropenem against cephalosporin-resistant Enterobacteriaceae.

BACKGROUND There is a need for new oral agents active against extended-spectrum beta-lactamase (ESBL) producers, as these increasingly cause community-onset infections. We therefore evaluated faropenem, a penem in Phase III development, against recently collected oxyimino-cephalosporin-resistant bacteria. METHODS We tested 847 consecutive cephalosporin-resistant Enterobacteriaceae collected a...