What are some examples of min-max scaling in Python?

Can you explain what min-max scaling is in Python?

Min-max scaling is a normalization technique that transforms features to a fixed range, usually [0, 1].

How can I implement min-max scaling in Python?

You can use the MinMaxScaler from the sklearn.preprocessing module. Here's a simple example:

from sklearn.preprocessing import MinMaxScaler
import numpy as np

# Sample data
data = np.array([[1, 2], [2, 3], [4, 5]])

# Create a scaler object
scaler = MinMaxScaler()

# Fit and transform the data
scaled_data = scaler.fit_transform(data)
print(scaled_data)

What are some use cases for min-max scaling?

Min-max scaling is commonly used in machine learning algorithms that require normalized data, such as neural networks and k-means clustering.

Are there any drawbacks to using min-max scaling?

Yes, min-max scaling can be sensitive to outliers, as they can significantly affect the scaling range.