Python Data Structures and Algorithms

Standard scalar

The mean values for the respective features in our initial dataset or table are 29.3, 92, and 38. To make all the data have a similar mean, that is, a zero mean and a unit variance across the data, we shall apply the standard scalar algorithm:

    stand_scalar =  preprocessing.StandardScaler().fit(data)     results = stand_scalar.transform(data)     print(results)

data is passed to the fit method of the object returned from instantiating the StandardScaler class. The transform method acts on the data elements in the data and returns the output to the results:

[[ 1.38637564 -1.10805456  0.19519899] [-0.93499753  1.31505377  1.11542277] [-0.45137812 -0.2069992  -1.31062176]]

Examining the results, we observe that all our features are now ...