More specifically, we use Theorem B.1 from (Sheffet, 2015) that states that given a matrix A whose all of its singular values at greater than T ( , δ) where T ( , δ) = 2B (√ 2r ln(4/δ) + 2 ln(4/δ) ) , publishing RA is ( , δ)differentially private for a r-row matrix R whose entries sampled are i.i.d normal Gaussians. Since we have that all of the singular values of A′ are greater than w (as spec...

In the process of vermicomposting, the earthworms Eisenia fetida have been exposed to various metals with different concentrations to study the effects on worms’ bioaccumulation. The study was carried within 14 days of exposure. Five different chemical compounds in various concentrations were added as mixture solutions to the experimental containers. Metals concentrations were measured in earth...

Linear regression is one of the most prevalent techniques in machine learning; however, it is also common to use linear regression for its explanatory capabilities rather than label prediction. Ordinary Least Squares (OLS) is often used in statistics to establish a correlation between an attribute (e.g. gender) and a label (e.g. income) in the presence of other (potentially correlated) features...

The Least Mean Square (LMS) algorithm, introduced by Widrow and Hoff in 1959 [12] is an adaptive algorithm, which uses a gradient-based method of steepest decent [10]. LMS algorithm uses the estimates of the gradient vector from the available data. LMS incorporates an iterative procedure that makes successive corrections to the weight vector in the direction of the negative of the gradient vect...

Partial least square (PLS) analysis is the most favourite tool in chemometrics to develop calibration models. PLS technique allows us decipher even complex systems by analysing all variables instead of looking at them one a time. not only capture maximum variation associated with predictor (i.e. spectra) and predicted concentration) but also maximises correlation between them. The present artic...