Python implementations for comparing different Regression Models and Plotting with their most common evaluation metrics. The purpose of this package is to help users plot the graph at ease with ...

Learn how to use Python to import, explore, choose, train, evaluate, and improve predictive models in four easy steps. Discover the libraries, algorithms, and techniques for modeling data.

Quantitative analysis model with Python. Extrapolate variance, standard deviation, correlation and beta of a list of securities in a few clicks. This model can help quantitative analysts in optimising ...

8.3. Regression diagnostics¶. Like R, Statsmodels exposes the residuals. That is, keeps an array containing the difference between the observed values Y and the values predicted by the linear model. A ...

Using Python's powerful libraries and frameworks, we can easily incorporate these steps into machine learning pipelines and automate the process of identifying and addressing bias in our models. As ...

This paper presents a Python-driven graphical user interface (GUI) explicitly crafted for benchmarking the electromagnetic transient (EMT) models of inverter-based resources (IBRs) across ...