ef perceptron_single_step_update( feature_vector, label, current_theta, current_theta_0):
def perceptron_single_step_update(
feature_vector,
label,
current_theta,
current_theta_0):
"""
Properly updates the classification parameter, theta and theta_0, on a
single step of the perceptron
Args:
feature_vector - A numpy array describing a single data point.
label - The correct classification of the feature vector.
current_theta - The current theta being used by the perceptron
algorithm before this update.
current_theta_0 - The current theta_0 being used by the perceptron
algorithm before this update.
Returns: A tuple where the first element is a numpy array with the value of
theta after the current update has completed and the second element is a
real valued number with the value of theta_0 after the current updated has
completed.
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