Ensemble Models: What Are They and When Should You Use Them? | Built In

A Complete Guide to Ensemble Learning

AdaboostIn Adaboost, each model has different say/importance according to the error it has made whilepredicting the training data.This is depicted in the following equation: α= 0.5 ln((1-TOTAL ERROR)/(TOTAL ERROR))With respect to this, consider the following statements and choose the correct:1. The classifier weight grows exponentially as the error approaches 0. Better classifiers are givenexponentially more weight.2. The classifier weight is 0.5 if the error rate is 0.5. This is because the cla

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