There are approximately a dozen common regression techniques. The most basic technique is called linear regression, or sometimes multiple linear regression ... trained using iterative stochastic ...

The percentage of time during a trip when drivers were 16.1 kph under the speed limit was modeled as the dependent variable using beta regression. The variables that resulted in the best fit model ...

Abstract: The cost function minimization is essential in finding a good model for linear regression. This paper works on prototyping and examining the minimizing cost function's two known algorithms ...

We propose a method for estimating glacier flowlines through local linear regression gradient descent (gd-flow ... gd-flow further improves gd-flow by leveraging the accuracy of multiple window sizes.

demo.py gives you an insight to use the module LinearRegression, you can use it to make and fit your models If you are not familiar with Git and GitHub, you can simply download the zip file of the ...