Logistic regression employs a logistic function with a sigmoid (S-shaped) curve to map linear combinations of predictions and their probabilities. Sigmoid functions map any real value into ...

Linear regression is a statistical method used to understand the relationship between an outcome variable and one or more explanatory variables. It works by fitting a regression line through the ...

else: actuals.insert(i,1) Python has many terse one-line syntax shortcuts because the language was designed to be used interactively. Training the Logistic Regression Model Training the model begins ...

In this video, we will implement Multiple Linear Regression in Python from Scratch on a Real World House Price dataset. We will not use built-in model, but we will make our own model. This can be ...

Unfortunately, our linear regression fit is not robust. Consider a child of height H = 100 cm who does not play professional basketball (Fig. 2a).

Physics and Python stuff. Most of the videos here are either adapted from class lectures or solving physics problems. I really like to use numerical calculations without all the fancy programming ...

I use Python 3 and Jupyter Notebooks to generate plots and equations with linear regression on Kaggle data. I checked the correlations and built a basic machine learning model with this dataset.

Lawless and Singhal (1978, Biometrics 34, 318-327) proposed a method for best subsets selection for nonnormal models. We develop a method for logistic regression that may be performed with any best ...

Logistic regression is a machine learning technique for binary classification. For example, you might want to predict the sex of a person (male or female) based on their age, state where they live, ...