Description
Describe the bug
By setting the copy=False, ndarray data has not changed unexpectedly
Steps/Code to Reproduce
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import sklearn.preprocessing as pre
np.random.seed(10)
data = np.random.randint(1, 10, size=(5, 3))
print(data)
pre.minmax_scale(data, feature_range=(0, 1), axis=0, copy=False)
print(data)Expected Results
A reasonable explanation about the copy parameter of minmax_scala funciton
Actual Results
There are no warings and errors, just the result is not wrong!
Versions
Python dependencies:
sklearn: 1.3.0
pip: 23.2.1
setuptools: 65.5.0
numpy: 1.25.2
scipy: 1.11.2
Cython: None
pandas: 2.0.3
matplotlib: 3.7.2
joblib: 1.3.2
threadpoolctl: 3.2.0