instead of the functional distribution of income per se. The paper discusses how abstraction is used in science and economics …, and employs the criteria proposed by Lawson (1989) for what constitutes an appropriate abstraction. Based on this …

paper discusses how abstraction is used in science and economics, and uses the criteria proposed by Lawson (1989) for what … constitutes an appropriate abstraction. Based on this discussion, it concludes that the criticisms are weak, although the issues …

production stages. Thus, supervised machine learning methods such as classification can viably predict product compliance quality … manufacturing processes, the adoption of classification methods to predict the overall compliance of production batches has not been … extensively investigated. This paper aims to design machine learning based classification methods for quality compliance and …

is a longitudinal consistency in classification choice within each company, there is no consistency among the companies … providing comparative results for Estonia, Latvia and Lithuania in financial statement preparers' classification judgement. …

two different statistical methods of classification (artificial neural network and Support Vector Machine). We use a … Neural Network models outperform the SVM models in terms of global good classification rates and of reduction of Error type I …. In fact, the good classification rates are respectively 90.2% (NNM) and 70.13% (SVM) for the in-sample set and the error …

with aspects of definition, classification, and aggregation that can be corrected. The main issue, however, is the lack of …

-step hybrid model based on machine learning methods for clustering and classification. First, we assign price states to historical …-nearest neighbors or random forest classification. We apply our model to real corn futures data and generate price scenarios via a Monte …