Evaluating Economic Performance with Soft Regression

EasyChair Preprint 777

Abstract

This study demonstrates effective data mining tool under severe limitations of data availability. We present a soft computing method for evaluating economic performance. To avoid computational explosion, we utilize intervals. This will reduce the number attributes in the dataset. Utilizing intervals allows us to overcome difficult modeling problems such as large quantity of missing data, substantial outliers, etc. Finally, case study of evaluating economic performance of the Soviet led East European bloc is presented. In spite of highly unreliable and inaccurate data provided by the officials of the bloc, the method presented here allows to reach solid and reliable conclusions.

Keyphrases: Cross-national model, Data Mining, Fuzzy Logic, Soft Computing, Soft Regression

@booklet{EasyChair:777,
  author    = {Moti Schneider and Arthur Yosef and Eli Shnaider},
  title     = {Evaluating Economic Performance with Soft Regression},
  howpublished = {EasyChair Preprint 777},
  year      = {EasyChair, 2019}}