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Stacking Classifier Ensemble Classifiers Machine Learning
>> YOUR LINK HERE: ___ http://youtube.com/watch?v=sBrQnqwMpvA
Stacking is an ensemble learning technique to combine multiple classification models via a meta-classifier. The individual classification models are trained based on the complete training set; then, the meta-classifier is fitted based on the outputs -- meta-features -- of the individual classification models in the ensemble. The meta-classifier can either be trained on the predicted class labels or probabilities from the ensemble. • Let's first understand how a stacking classifier works and create a simple stacking classifier in Python. • If you do have any questions with what we covered in this video then feel free to ask in the comment section below I'll do my best to answer those. • If you enjoy these tutorials would like to support them then the easiest way is to simply like the video give it a thumbs up also it's a huge help to share these videos with anyone who you think would find them useful. • Be sure to subscribe for future videos thank you all for watching. • You can find me on: • GitHub - https://github.com/bhattbhavesh91 • Medium - / bhattbhavesh91 • • #stackingclassifier #ensemble #metaclassifier
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