import numpy as np
[docs]class Normalizer:
[docs] def normalize(X):
'''normalizes a ndarray'''
X = (X - np.amin(X))/(np.amax(X)-np.amin(X))
return X
[docs]class MinMaxScaler:
[docs] def scale(X, a=0, b=1):
"""
Scales a ndarray in a set of values
Parameters:
X (ndarray): ndarray of the data to be scaled
a (float): float of the minimum value
b (float): float of the maximum value
Returns:
ndarray of the scaled values
"""
X = a + ((X - np.amin(X))*(b-a))/(np.amax(X)-np.amin(X))
return X
[docs]class MeanNormalizer:
[docs] def mean_normalize(X):
'''mean normalizes a ndarray'''
X = (X - np.average(X))/(np.amax(X)-np.amin(X))
return X
[docs]class StandardScaler:
[docs] def standard_scale(X):
"""Standard scales a ndarray"""
sd = np.std(X)
av = np.average(X)
return (X - av)/sd