Comparative Evaluation of Learning Algorithms and the Effect of Their Characteristics on Performance

Released on by Yossi Hohashvili
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  • Comparative Evaluation of Learning Algorithms and the Effect of Their Characteristics on Performance Book Detail

  • Author : Yossi Hohashvili
  • Release Date : 2020
  • Publisher :
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  • File Size : 18,18 MB
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Comparative Evaluation of Learning Algorithms and the Effect of Their Characteristics on Performance by Yossi Hohashvili PDF Summary

Book Description: This research contributes to the literature by examining possible criteria for evaluating algorithms and assessing their fit for certain decisional problems with respect to available data resources. Such a comparison would lead to a better understanding and better decision-making in the business domain. This research compared 10 main algorithms that represent leading machine learning and traditional statistics algorithms, and over 18 datasets for regression and classification problems. The datasets have been split randomly into 720 sub datasets in order to control the data richness effect over the compression. The results indicate that most leading algorithms are ensemble trees at all levels of analysis and XGBoost is the leading algorithm; however, Random Forest is comparable in terms of accuracy but faster by a significant measure. -- From the abstract.

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