Machine Learning, Logistic Regression, Non Linear.
the decision boundary for the following c values We generate 1000 data points for each class based on the above function and apply logistic regression to that data to see what it predicts for the decision boundary. pipenv run python ./polynomial.py 1000 2.25 -3.0 -18.0 35.0 -64.0 50.0 Figure 2