The Purpose of this project is to practice with a single neuron decision boundary and learning rule. It will display a decision boundary of single neuron.
Python Version used:- 3.6
This program contains 3 sliders, 2 buttons, and one drop down selection box.
• Sliders:- Slider 1: Changes w1 (first weight) between -10 and 10. Default value = 1 Slider 2: Changes w2 (second weight) between -10 and 10. Default value = 1 Slider 3: Changes b (bias between -10 and 10. Default value=0
• Buttons:- Button1: Train. Clicking this button adjusts the weights and bias for 100 steps using the learning rule. Wnew =Wold+ epT where e = t – a Button 2: Create random data. Assuming that there are only two possible target values 1 and -1 (two classes), this button creates 4 random data points (two points for each class). The range of data points should be from -10 to 10 for both dimensions.
• Drop Down Selection:- The drop down box allows the user to select between three transfer functions (Symmetrical Hard limit, Hyperbolic Tangent, and Linear)