perceptron

perceptron contains implementations of the perceptron with online learning, the average perceptron, and a polynomial kernel perceptron.

Requirements:

• numpy 1.17.2

• pandas 0.25.1

• progressbar2 3.37.1

Usage:

from models.perceptron import Perceptron

model = Perceptron(train='pa2_train_clean.csv',
                   validation='pa2_valid_clean.csv',
                   test='pa2_test_no_label_clean.csv',
                   label='label', # Specify target name
                   mod_type='online', # Choose model type
                   max_iter=15, # Set maximum iterations for training
                   p=None) # If using polynomial kernel, set degree

learned_model = model.train_model()

Data:

The data/ folder contains .csv files with training, validation, and test sets.

To run models:

• run_part0.py runs pre-processing.
• run_part1.py runs online perceptron.
• run_part2.py runs average perceptron.
• run_part3.py runs perceptron using a polynomial kernel.

python main.py will run all four parts in order, output will be saved in model_output folder.