The credit scoring model development has become a very important issue, as the credit industry is highly competitive. Therefore, considerable credit scoring models have been widely studied in the areas of statistics to improve the accuracy of credit scoring during the past few years. This study constructs a hybrid SVM-based credit scoring models to evaluate the applicant’s credit score accordin...

Automatic essay scoring is nowadays successfully used even in high-stakes tests, but this is mainly limited to holistic scoring of learner essays. We present a new dataset of essays written by highly proficient German native speakers that is scored using a fine-grained rubric with the goal to provide detailed feedback. Our experiments with two state-of-the-art scoring systems (a neural and a SV...

Finite mixture distributions arise naturally in many applications including clustering and classification. Since they usually do not yield closed forms for maximum likelihood estimates (MLEs), numerical methods using the well known Fisher Scoring or Expectation-Maximization algorithms are considered. In this work, an approximation to the Fisher Information Matrix of an arbitrary mixture of mult...

Spelling errors occur frequently in educational settings, but their influence on automatic scoring is largely unknown. We therefore investigate the influence of spelling errors on content scoring performance using the example of the short answer data set of the Automated Student Assessment Prize (ASAP). We conduct an annotation study on the nature of spelling errors in the ASAP dataset and util...

Methods The monitoring plan in a large long-term multicentre international trial required that sites received routine monitoring visits every nine months. Oversight of this trial was augmented by central statistical monitoring that identified high scoring sites as priority for further investigation. To validate this approach high scoring sites, and some low scoring sites (in the same countries)...

Automated essay scoring is one of the most important educational applications of natural language processing. Recently, researchers have begun exploring methods of scoring essays with respect to particular dimensions of quality such as coherence, technical errors, and relevance to prompt, but there is relatively little work on modeling organization. We present a new annotated corpus and propose...

 Abstract Background: Clinical Risk Index of Babies (CRIB), Score for Neonatal Acute Physiology (SNAP), an update of the Clinical Risk Index for Babies score (CRIB II) and Score for Neonatal Acute Physiology - Perinatal Extension (SNAP-PE) are scoring devices developed in neonatal intensive care units. This study reviewed these scoring systems in critically ill neonates to determine how well th...

Objective: This study aimed to Prepare an educational program based on the overlap and the integration of the random exercise method with the variable exercise method and the intensive exercise method adapted to the capabilities of the research sample and Recognize the effect of the educational program on developing the skill performance and scoring accuracy of the research sample in the futsal...

Automated short answer scoring is increasingly used to give students timely feedback about their learning progress. Building scoring models comes with high costs, as stateof-the-art methods using supervised learning require large amounts of hand-annotated data. We analyze the potential of recently proposed methods for semi-supervised learning based on clustering. We find that all examined metho...