Support vector machines (SVM) is an effective tool for building good credit scoring models. However, the performance of the model depends on its parameters’ setting. In this study, we use direct search method to optimize the SVM-based credit scoring model and compare it with other three parameters optimization methods, such as grid search, method based on design of experiment (DOE) and genetic ...

Tandem mass spectrometry (MS/MS) has become a standard way for identifying peptides and proteins. A scoring function plays an important role in the MS/MS data analysis. De novo sequencing is the computational step to derive a peptide sequence from an MS/MS spectrum, normally by constructing the peptide that maximizes the scoring function. A number of polynomial time algorithms have been develop...

The predominant language model for speech recognition is n-gram language model, which is locally learned and usually lacks global linguistic information such as long-distance syntactic constraints. We first explore two n-best re-scoring approaches for Mandarin speech recognition to overcome this problem. The first approach is linear re-scoring that can combine several language models from vario...

cumulative embryo score (ces) is one of the many embryo scoring methods which have been developed to help clinicians to transfer high quality embryos and predict pregnancy rate in assisted reproductive techniques (art) cycles. regarding the existing difference in ces calculation this study was done to compare two methods in order to determine the more practical and preferable one. in a retrospe...

Scoring models yield continuous predictions instead of sharp classifications. Scoring customers for profitability, loyalty, or product affinity corresponds to an inductive fuzzy classification: The model represents a continuous membership function mapping the set of customers into the fuzzy set of interesting customers – the fuzzy target group. This chapter presents a method for membership func...

In this paper, a paradigm for the automatic scoring of flat tongue and raised tongue in computer-assisted Mandarin learning is presented. In this paradigm, distinctive features of Mandarin is used to distinguish the two classes consonants and score them. The confusion of them mainly results from different articulation places. The method based on the distributing of concentrated frequency area i...

This article presents a new model for scoring alternatives from "contest" outcomes. The model is a generalization of the method of paired comparison to accommodate comparisons between arbitrarily sized sets of alternatives in which outcomes are any division of a fixed prize. Our approach is also applicable to contests between varying quantities of alternatives. We prove that under a reasonable ...

We describe a system that grades learner answers in reading comprehension tests in the context of foreign language learning. This task, also known as short answer scoring, essentially requires determining whether a semantic entailment relationship holds between an individual learner answer and a target answer; thus semantic information is a necessary part of any automatic short answer scoring s...

We present an approach to textual classification based on the suffix tree data structure and apply it to spam filtering. A method for scoring of documents using the suffix tree is developed and a number of scoring and score normalisation functions are tested. Our results show that the character level representation of documents and classes facilitated by the suffix tree significantly improves c...

The current methods of turfgrass evaluations are often based on human-based assessment methods. However, eliminating subjective errors from such evaluations is often impossible. This research compared the accuracy of human-based and digital image processing-based methods for quality assessment of turfgrasses. Four turfgrass plots were evaluated using the two mentioned methods. In the human-base...