def plot_toy_results(algo_name, thetas):
try:
utils.plot_toy_data(algo_name, toy_features, toy_labels, thetas)
except Exception, e:
print 'Error in utils.plot_toy_data function'
type, value, tb = sys.exc_info()
traceback.print_exc()
pdb.post_mortem(tb)
def plot_toy_results(algo_name, thetas):
utils.plot_toy_data(algo_name, toy_features, toy_labels, thetas)
def plot_toy_results(algo_name, thetas):
print('theta for', algo_name, 'is', ', '.join(map(str, list(thetas[0]))))
print('theta_0 for', algo_name, 'is', str(thetas[1]))
utils.plot_toy_data(algo_name, toy_features, toy_labels, thetas)
def plot_toy_results(algo_name, thetas):
utils.plot_toy_data(algo_name, toy_features, toy_labels, thetas)
import project1 as p1
from project1 import perceptron, average_perceptron, pegasos
import utils
import numpy as np
import numpy.testing as npt
import re
toy_features, toy_labels = toy_data = utils.load_toy_data('toy_data.tsv')
T = 10
L = 0.2
thetas = perceptron(toy_features, toy_labels, T)
print(thetas)
utils.plot_toy_data("Perceptron", toy_features, toy_labels, thetas)
thetas = average_perceptron(toy_features, toy_labels, T)
print(thetas)
utils.plot_toy_data("Average Perceptron", toy_features, toy_labels, thetas)
thetas = pegasos(toy_features, toy_labels, T, L)
print(thetas)
utils.plot_toy_data("Pegasos", toy_features, toy_labels, thetas)
"""
Comparison between convergence of perceptron, average perceptron,
and pegasos linear classifiers on a toy dataset
Created on Mon Sep 7 17:43:05 2020
@author: mohamad jalalimanesh
"""
import matplotlib.pyplot as plt
import matplotlib.animation as animation
import numpy as np
from utils import create_toy_data, plot_toy_data
from perceptron import perceptron
from averaged_perceptron import average_perceptron
from pegasos import pegasos
features, labels = create_toy_data(350)
fig, ax = plot_toy_data(features, labels)
xmin, xmax = plt.axis()[:2]
x = np.linspace(xmin, xmax)
lines = []
plotlabels = ['perceptron', 'average perceptron', 'pegasos']
plotcols = ["black", "m", "g"]
for index in range(3):
lobj, = ax.plot(x, np.zeros(x.shape), lw=3, color=plotcols[index], \
label=plotlabels[index])
lines.append(lobj)
ax.set_title('epoch = {}'.format(str(0)))
ax.legend(loc='upper right')
