Stacking Classifier | Ensemble Classifiers | Machine Learning - YouTube Bhavesh Bhatt

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 - https://medium.com/@bhattbhavesh91 #stackingclassifier #ensemble #machinelearning #version2 #python #deeplearning #datascience #youtube

Stacking Classifier | Ensemble Classifiers | Machine Learning - YouTube
24 Likes	24 Dislikes
575 views views	4,589 followers
Education	Upload TimePublished on 9 May 2019