shythm / uos-simple-mlp

Simple Multi-Layer Perceptron(MLP) with forward and backward propagation

2023-2 Artificial Intelligence Coding

• 2019920037 컴퓨터과학부 이성호

Assignment 3

• Experimental Tasks

  1. Implement AND, OR, and XOR gates
  2. Use donut shaped data (next slide)

• Let the number of layers and the number of nodes per layer be variables.

• Implement the calculation of one layer as a function.

• Save the weight to a file in a matrix format

• Show the learning process (X1, X2 two-dimensional straight line graphs).

  • Plot straight lines of a few nodes.
  • In this repository, it shows the learning process using contour plot (instead of straight line graph).

• Show error graph as a function of iteration

How to run

To run this code, you need to install the following packages: numpy, matplotlib. You can install them using pip with requirements.txt file.

pip install -r requirements.txt

How to run the code:

$ python main.py
Usage: python main.py [dataset] [hidden nodes] [activation] [learning rate] [epochs] [check epoch]
Example: python main.py donut 4 sigmoid 0.1 10000 2000
Available activation functions: sigmoid, relu, step
Available dataset: donut, and, or, xor
This program learns the given data using two-layer perceptron.

Examples:

python main.py donut 4 sigmoid 0.4 10000 2000

python main.py xor 4 sigmoid 0.4 10000 2000