PLEASE USE MATLAB and explain.

3. Construct a quadratic error function using a learn model with a soft threshold (sigmoid) function for augmented feature vectors in n+1 dimensions. Derive a gradient decent algorithm for learning the weights. Write a program using either Matlab or Python to learn the weights using the training samples you generate from Prob. 2. Plot the resulting decision boundary. 3. Construct a quadratic error function using a learn model with a soft threshold (sigmoid) function for augmented feature vectors in n+1 dimensions. Derive a gradient decent algorithm for learning the weights. Write a program using either Matlab or Python to learn the weights using the training samples you generate from Prob. 2. Plot the resulting decision boundary