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Aj e bari eid ka din ha, aur aj e yeh misaal ... <3
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Done
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Done
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I learned in this video Ensemble (Bagging (Bootstrap Aggregating), Bosting, and Stacking(Stacked Generalization))
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I learned in this lecture Ensemble Methods (Bootstrap Aggregating), Bosting, and Stacking(Stacked Generalization).
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This lecture contains the new concept of Ensemble Algorithms which is near to best in place of neural networks.
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AOA, I learned in this lecture about the ML algorithm of Ensemble Methods and its types
Which are1- Bagging ( aggregation) ( parallel tree growing with sub-samples )
2- Boosting ( sequential tree growth with weighted samples )
3- Stacking ( Stacked Generalization )And also learned the uses of Ensemble Algorithms which are1-For Accuracy
2-For Stability
3-For Reduced Overfitting
I also learned about the applications of Ensemble Algorithms which are1- Finance (for credit scoring and algorithmic trading)
2- Healthcare (for disease prediction and diagnosis)
3- E-commerce (for recommendation systems)
4-Stock market ( prediction )I also learned the disadvantages of the Ensemble Algorithm which are1-Complexity ( computationally expensive and take more time )
2-Interpretability ( harder to interpret )
3-Parameter Tuning ( requires careful tuning of parameters )I also learned the advantages of the Ensemble Algorithm which are1-Enhanced accuracy of the model
2-Robust the model
3-Generalized the model
4-Improve the model
5-Versatility ( used for both classification and regression tasks)
6-Easy to use ( requires little tuning of parameters )ALLAH PAK aap ko sahat o aafiat wali lambi umar ata kray aor ap ko dono jahan ki bhalian naseeb farmaey,Ameen.
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