In this section, we will walk through the implementation of logistic regression in Python within the packtml
package. We will start off with a brief recap of what logistic regression seeks to accomplish and then go over the source code and look at an example.
Note
Recall that logistic regression seeks to classify a sample into a discrete category, also known as classification. The logistic transformation allows us to transform the log odds that we get from the inner product of our parameters and X
.
Notice that we have three Python files open. One is extmath.py
, from within the utils
directory inside of packtml
; another is simple_logistic.py
, from within the regression
library in packtml
; and the final one is an example_logistic_regression.py
file, inside the examples
directory and regression
.
We will dive right into the code base using the following steps:
- We will start with the
extmath.py
file. There are two functions that we will be using here...