Implementing a 2-class Classification Neural Network with a Single Hidden Layer
Visualising the dataset using matplotlib. The data looks like a “flower” with some red (label y=0) and some blue (y=1) points. Number of training examples is 400. The goal is to build a model to fit this data. The Dataset contains a numpy-array (matrix) X that contains the features (x1, x2) and a numpy-array (vector) Y that contains your labels (red:0, blue:1). The size of hidden layer is 4.
The Neural Network model with one hidden layer has learnt the leaf patterns of the flower!
Accuracy is 90%