Essentials of Machine Learning Algorithms (with Python and R Codes) - Part 10
Gradient Boosting & AdaBoost
GBM & AdaBoost are boosting algorithms used when we deal with plenty of data to make a prediction with high prediction power. Boosting is an ensemble learning algorithm which combines the prediction of several base estimators in order to improve robustness over a single estimator. It combines multiple weak or average predictors to a build strong predictor. These boosting algorithms always work well in data science competitions like Kaggle, AV Hackathon, CrowdAnalytix.
Python Code:
R Code:
GradientBoostingClassifier and Random Forest are two different boosting tree classifier and often people ask about the difference between these two algorithms.