What is the difference between Standard Error and Weighted Standard Error in TF learn

This recipe explains what is the difference between Standard Error and Weighted Standard Error in TF learn

Recipe Objective

This recipe explains the difference between Standard Error and Weighted Standard Error.

Learn to Implement Customer Churn Prediction Using Machine Learning in Python

Standard Error

It is useful to compute linear regression. It calculates the coefficient of determination.
Its syntax is: tflearn.metrics.R2 (name=None) where its argument is name which is name of display.

# Standard Error
# To be used with TFLearn estimators
standard = R2()
op = op(my_network, metric=standard)

Weighted Standard Error

It is useful to compute linear regression. It calculates the coefficient of determination.
Its syntax is: tflearn.metrics.WeightedR2 (name=None) where its argument names which is name of display.

# Weighted Standard Error
# To be used with TFLearn estimators
weight = WeightedR2()
op = op(my_network, metric=weight)

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