Skip to content

@suzaku /logistic_regression.py
Created

Embed URL

HTTPS clone URL

Subversion checkout URL

You can clone with
or
.
Download ZIP
import random
import math
import csv
def hypothesis(params, features):
z = sum(p * f for p, f in zip(params, features))
return 1 / (1 + math.e ** -z)
def logistic_regression(learning_rate, samples):
params = [random.random()] * len(samples[0].features)
for s in samples:
error = s.target - hypothesis(params, s.features)
params = [p + (learning_rate * error * f) for p, f in zip(params, s.features)]
return params
class Sample(object):
def __init__(self, target, features):
self.target = target
self.features = features
if __name__ == '__main__':
with open("wine.data") as f:
record = csv.reader(f)
rows = (map(float, row) for row in record)
samples = [Sample(r[0], r[1:]) for r in rows]
learning_rate = 0.1
params = logistic_regression(0.1, samples)
for i, s in enumerate(samples):
print i, hypothesis(params, s.features)
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Something went wrong with that request. Please try again.