pyqt_data_analysis/libdataanalysis/8-Kmeans代码实现/utils/features/generate_polynomials.py

45 lines
1.4 KiB
Python

"""Add polynomial features to the features set"""
import numpy as np
from .normalize import normalize
def generate_polynomials(dataset, polynomial_degree, normalize_data=False):
"""变换方法:
x1, x2, x1^2, x2^2, x1*x2, x1*x2^2, etc.
"""
features_split = np.array_split(dataset, 2, axis=1)
dataset_1 = features_split[0]
dataset_2 = features_split[1]
(num_examples_1, num_features_1) = dataset_1.shape
(num_examples_2, num_features_2) = dataset_2.shape
if num_examples_1 != num_examples_2:
raise ValueError('Can not generate polynomials for two sets with different number of rows')
if num_features_1 == 0 and num_features_2 == 0:
raise ValueError('Can not generate polynomials for two sets with no columns')
if num_features_1 == 0:
dataset_1 = dataset_2
elif num_features_2 == 0:
dataset_2 = dataset_1
num_features = num_features_1 if num_features_1 < num_examples_2 else num_features_2
dataset_1 = dataset_1[:, :num_features]
dataset_2 = dataset_2[:, :num_features]
polynomials = np.empty((num_examples_1, 0))
for i in range(1, polynomial_degree + 1):
for j in range(i + 1):
polynomial_feature = (dataset_1 ** (i - j)) * (dataset_2 ** j)
polynomials = np.concatenate((polynomials, polynomial_feature), axis=1)
if normalize_data:
polynomials = normalize(polynomials)[0]
return polynomials