Detection of Online Fake News Using Blending Ensemble Learning

Algorithm 1

Blending ensemble algorithm.

(1)	Split the dataset.
	The dataset is split into test and train sets.
(2)	Construct the base models.
(3)	Train the blending ensemble.
Repeat
Fit on the training set.
Make prediction on holdout set.
Store the predictions as input for blending until the end of base models.
Build a 2D array using the stored predictions.
Create the blending model.
Fit the blending model on the predictions from base models.
(4)	Make predictions with the blending ensemble.
Repeat
Make prediction with base model on test set.
Store the prediction until the end of base models. Build a 2D array using the stored predictions.
(5)	Evaluate the predictions.