Two Scalers, One Value

Statistics for MLEasy+10 XP+10

A single numeric feature is measured across a training set. Over that training set the feature has

$\mu = 50, \qquad \sigma = 12, \qquad x_{min} = 20, \qquad x_{max} = 80$

You fit two scalers on this training set: a Z-score standardizer

$z = \frac{x - \mu}{\sigma}$

and a Min-Max scaler that maps the feature onto $[0, 1]$

$x' = \frac{x - x_{min}}{x_{max} - x_{min}}$

One training row has the raw value $x = 68$ .

What does each fitted scaler output for this row?

Select all that apply.

Comparing Scaling Transformations

Explore how data positions and coordinate axes shift under standardization and Min-Max scaling. Hover over data points to check coordinate values.

Mode: Raw

X Range: [1.0, 5.0]

Y Range: [10.0, 40.0]

Notice how the scale of Y is 10x larger than X. Distance calculations will be biased towards Y.