Can anyone explain me StandardScaler?

python machine-learning scikit-learn scaling standardized
nitinvijay23 picture nitinvijay23 · Nov 23, 2016 · Viewed 158.6k times · Source

I am unable to understand the page of the StandardScaler in the documentation of sklearn.

Can anyone explain this to me in simple terms?

Answer

user6903745 picture user6903745 · Nov 23, 2016

The idea behind StandardScaler is that it will transform your data such that its distribution will have a mean value 0 and standard deviation of 1.
In case of multivariate data, this is done feature-wise (in other words independently for each column of the data).
Given the distribution of the data, each value in the dataset will have the mean value subtracted, and then divided by the standard deviation of the whole dataset (or feature in the multivariate case).

Related questions

How to compute precision, recall, accuracy and f1-score for the multiclass case with scikit learn?

I'm working in a sentiment analysis problem the data looks like this: label instances 5 1190 4 838 3 239 1 204 2 127 So my data is unbalanced since 1190 instances are labeled with 5. For the classification Im using scikit's SVC. The problem is I do not know how to …

Read More
Accuracy Score ValueError: Can't Handle mix of binary and continuous target

I'm using linear_model.LinearRegression from scikit-learn as a predictive model. It works and it's perfect. I have a problem to evaluate the predicted results using the accuracy_score metric. This is my true Data : array([1, 1, 0, 0, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0]) My predicted Data: array([ 0.07094605, 0.1994941 , 0.19270157, 0.13379635, 0.04654469, 0.09212494, 0.19952108, 0.12884365, 0.15685076, …

Read More
Save classifier to disk in scikit-learn

How do I save a trained Naive Bayes classifier to disk and use it to predict data? I have the following sample program from the scikit-learn website: from sklearn import datasets iris = datasets.load_iris() from sklearn.naive_bayes import …

Read More