You are performing feature scaling by using the scikit-learn Python library for x.1 x2, and x3 features

HOTSPOT

You are performing feature scaling by using the scikit-learn Python library for x.1 x2, and x3 features.

Original and scaled data is shown in the following image.

Use the drop-down menus to select the answer choice that answers each question based on the information presented in the graphic. NOTE: Each correct selection is worth one point.

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Answer:

Explanation:

Box 1: StandardScaler

The StandardScaler assumes your data is normally distributed within each feature and will scale them such that the distribution is now centred around 0, with a standard deviation of 1.

Example:

All features are now on the same scale relative to one another.

Box 2: Min Max Scaler

Notice that the skewness of the distribution is maintained but the 3 distributions are brought into the same scale so that they overlap.

Box 3: Normalizer

Reference: http://benalexkeen.com/feature-scaling-with-scikit-learn/