A metal harvest to power the world

Volume: 37, Pages: 5 - 6
Published: Jul 1, 2020
Abstract
This paper presents a new Quantitative Structure-Activity Relationship (QSAR) model based on Extreme Learning Machine (ELM) to predict the biological activity of the benchmark Escape-Data sets compounds in order to provide an effective learning solution for regression analysis. The pre-processing phase of this model has been performed for the chemo-genomics datasets using the k-Nearest Neighbours (k-NN) algorithm to predict missing values of the...
Paper Details
Title
A metal harvest to power the world
Published Date
Jul 1, 2020
Volume
37
Pages
5 - 6
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