Measuring the Effectiveness of Hidden Context Usage by Machine Learning Methods under Conditions of Increased Entropy of Noise
Maciej Huk · 2017
The context can be defined as the data that is needed for solving given problem. In this view the effectiveness of context search and usage is one of the key factors of computational awareness - to solve given problems computational systems need to become aware of the related context. In this paper we concentrate on the estimation of context usage effectiveness of selected machine learning algorithms for data created with injection of hidden context masked by noise of different levels of entropy.