Achint08 / perceptron-neural-network

One layer Perceptron Neural Network using numpy.

Perceptron Neural Network with one layer

We are going to implement stochastic, batch and mini batch gradient descent using basic data science libraries.

How to run?

Note: Please use Python3

Install the requirements:

pip install -r requirements.txt

Run the following command to run the code:

python main.py

For each gradient descent type, graphs for MSE per iteration will be stored in plots/ directory after running the code.

Directory Structure

• main.py - Entry level for the project
• layer.py - Contains layer class for each layer
• neural_network.py - Contains neural network class with added layers
• plots/ - Contains plots for MSEs

Assumptions

• We've divided data set in ration of train: test :: 8: 2.
• We're considering bias as a weight for a feature, instead of computing it individually. So, we've added 1.0 to the feature set along with the four feature. The weights for this data point will compensate for bias value.
• Mini batch size = 12
• Total epochs = 1000
• Using sigmoid as activation functon with threshold = 0.5
• Hyperparameters for mini-batch and stochastic:
  • t0 = 0.1
  • t1 = 5

Thank you :)