credit decisions are extremely vital for any type of financial institution because it can stimulate huge financial losses generated from defaulters. credit scoring models are decision support systems that take a set of predictor variables as input and provide a score as output and creditors use these models to justify who will get credit and who will not. many different credit scoring models ha...

In this paper, we introduce and test two new sequence-based protein scoring systems (i.e. S1, S2) for assessing the likelihood that a given protein hybrid will be functional. By binning together amino acids with similar properties (i.e. volume, hydrophobicity and charge) the scoring systems S1 and S2 allow for the quantification of the severity of mismatched interactions in the hybrids. The S2 ...

A profile comparison method with position-specific scoring matrix (PSSM) is one of the most accurate alignment methods. Currently, cosine similarity and correlation coefficient are used as scoring functions of dynamic programming to calculate similarity between PSSMs. However, it is unclear that these functions are optimal for profile alignment methods. At least, by definition, these functions ...

PURPOSE A number of previous studies have shown inconsistencies between sub-scale scores and component summary scores using traditional scoring methods of the SF-36 version 1. This study addresses the issue in Version 2 and asks if the previous problems of disagreement between the eight SF-36 Version 1 sub-scale scores and the Physical and Mental Component Summary persist in version 2. A second...

credit scoring is a kind of binary classification problem that contains important information for manager to make a decision in particularly in banking authorities. obtained scores provide a practical credit decision for a loan officer to classify clients to reject or accept for payment loan. for this sake, in this paper a data envelopment analysis- discriminant analysis (dea-da) approach is us...

In this study, we present a pronunciation scoring method for second language learners of English (hereafter, L2 learners). This study presents a method using both confidence scoring and classifiers. Classifiers have an advantage over confidence scoring for specialization in the specific phonemes where L2 learners make frequent errors. Classifiers (Landmark-based Support Vector Machines) were tr...

This paper proposes a novel automatic pronunciation scoring framework using learning to rank. Human scores of the utterances are treated as ranks and are used as the ranking ground truths. Scores generated from various existing scoring methods are used as the features to train the learning to rank function. The output of the function is then segmented by the proposed DP-based method and hence b...

BACKGROUND The aims of this study were to compare various genotypic scoring systems commonly used to predict virological outcome to etravirine, and examine their concordance with etravirine phenotypic susceptibility. METHODS Six etravirine genotypic scoring systems were assessed: Tibotec 2010 (based on 20 mutations; TBT 20), Monogram, Stanford HIVdb, ANRS, Rega (based on 37, 30, 27 and 49 mut...