Supplementary material Quantitative evaluation of confidence measures in a machine learning world

Verification of unemployment benefits’ claims using Classifier Combination method

Unemployment insurance is one of the most popular insurance types in the modern world. The Social Security Organization is responsible for checking the unemployment benefits of individuals supported by unemployment insurance. Hand-crafted evaluation of unemployment claims requires a big deal of time and money. Data mining and machine learning as two efficient tools for data analysis can assist ...

Inferring species interaction networks from species abundance data: A comparative evaluation of various statistical and machine learning methods Supplementary Material

Presentation of an efficient automatic short answer grading model based on combination of pseudo relevance feedback and semantic relatedness measures

Automatic short answer grading (ASAG) is the automated process of assessing answers based on natural language using computation methods and machine learning algorithms. Development of large-scale smart education systems on one hand and the importance of assessment as a key factor in the learning process and its confronted challenges, on the other hand, have significantly increased the need for ...

Confidence Interval for the Difference in Classification Error

Evaluating classifiers with increased confidence can significantly impact the success of many machine learning applications. However, traditional machine learning evaluation measures fail to provide any levels of confidence in their results. In this paper, we motivate the need for confidence in classifier evaluation at a level suitable for medical studies. We draw a parallel between case-contro...

Identification of the Quantitative Dimensions of Supplementary Private Tutoring among High School Students

Identification of the Quantitative Dimensions of Supplementary Private Tutoring among High School Students   Y. Shiraavand* A. Ma’dandaar Aaraani, Ph.D.** I. Nikpey, Ph.D.***   To identify the quantitative dimensions of supplementary private tutoring, a cluster sample of 800 high school students was given a questionnaire on the subject. The collected data reveal that moti...