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K-Nearest Neighbors (KNN)
Understanding how to classify data points based on the majority class of their nearest neighbors. -
Bagging
Exploring the ensemble method of combining multiple models to improve stability and accuracy. -
AdaBoost
Learning how adaptive boosting combines weak classifiers to create a strong classifier. -
Random Forest
Understanding how an ensemble of decision trees can reduce variance and improve prediction accuracy.
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