I modelled the early evolution of COVID-19 as a logistic function with 6 parameters ... to find the optimal parameters θ *, i.e. those that minimize the objective (loss) function: where y are the data ...

Learn what is Logistic Regression Cost Function in Machine Learning and the interpretation behind it. Logistic Regression Cost function is "error" representation of the model. It shows how the ...

Huang, C. , Xiang, R. and Liu, X. (2025) The Association between Self-Perceived Ageing and Motoric Cognitive Risk Syndrome in Community-Dwelling Older People. Journal of Biosciences and Medicines, 13, ...

An objective function that includes operational and time costs was developed to quantify performance and determine the best collaboration level. Signal detection theory was applied to evaluate system ...

If you get the family in the car for a vacation, you would most assuredly plot a map to your destination. Wouldn't you? Then, if you want your business to develop and grow, why wouldn't you do the ...

Abstract: Rain prediction is challenging due to the complex combination of atmospheric factors. This paper presents the application of logistic regression modelling to predict rainfall the next day, ...

Implementing binary / multiple logistic regression models, for the well known mnist dataset while also creating the support vector machine(SVM) models ...