The fundamental building block of neural network is a model that mimic neuron cell. We can model this neuron using a model that output a value between 0 and 1, zero representing inactive cell and 1 ...

As part of a course in Probability and Statistic together with 4 collegues we tackled the problem of applying a Bayesian Probit Regression on the SAHearth dataset, estimating cefficients using ...

ABSTRACT: Background: Novel models for the assessment of non-linear data are being developed for the benefit of making better predictions from the data. Objective: To review traditional and modern ...

https://doi.org/10.2307/1182446 • https://www.jstor.org/stable/1182446 Copy URL Spector and Mazzeo assert that ordinary least squares regression analysis has been ...

Abstract: Probit regression was first proposed by Bliss in 1934 to study mortality rates of insects. Since then, an extensive body of work has analyzed and used probit or related binary regression ...