## This tutorial covers how to find the decision boundary in logistic regression classification with two features. |

- Select data series 'Class1' and data series 'Class2' on left panel [Points].
- Select menu item
**<Analysis><LogisticRegression>**. - Training dataset will be divided on two parts based on parameter Z value.
- In dialog on step 1 it will assign Z1=0 to points from Class1 and Z2=1 to points from Class2.
- We find the decision boundary curve line in form of X,Y polynomials.
- On step 2 select checked 'Reularization' and set parameter Lambda value to 20.
- Vary polynomial power parameters M and N
**to find best fit but to keep simple formula**. - to minimize percent of incorrect classified items in training and testing datasets.
- On step 2 select Class1 color, points in Class2 wll be brushed with inverted color.
- Close the dialog.