This project leverages data science skills, including least squares regression, causal inference techniques, and decision tree classification in order to answer to distinct questions regarding ...

Machine learning library for symbolic fitting: the unknown system/function is described via NARMAX algebraic expressions being linear combinations of arbitrary non-linear terms provided by the user ...

Abstract: In this paper, we proposed a new support vector machine for linear regression in the total least square sense (TLSSVR). Mathematical technique taken in the total leastsquare situations is ...

Abstract: This paper introduced an incomplete Latin square design that leads to difficulties in the analysis of variance (ANOVA). The aim was to determine the explicit and mathematical formulae for ...

In a variety of regression situations, there is interest in predicting the value of Y2, yet it is useful to model it using a square root transformation, such that Y rather than Y2 is regressed on one ...