Closed kapiblue closed 2 months ago
Preserve sparsity of the input data by using mean = 0.
This can be achieved by:
from sklearn.preprocessing import StandardScaler scaler = StandardScaler(with_mean=False) scaler.fit(data)
Examine the performance
https://stackoverflow.com/questions/21875518/features-scaling-and-mean-normalization-in-a-sparse-matrix
Preserve sparsity of the input data by using mean = 0.
This can be achieved by:
Examine the performance
https://stackoverflow.com/questions/21875518/features-scaling-and-mean-normalization-in-a-sparse-matrix