Understanding the working of Random Forest Classifier
Data science provides a plethora of classification algorithms such as Support Vector Machine, Naïve Bayes classifier, Logistic Regression, Decision Trees etc. But near the top of the classifier hierarchy is the Random Forest Classifier (there is also the random forest regressor but that is a topic for another day).
To understand the working of a Random Forest classifier, we need to first understand the concept of Decision Trees.
If you are not aware of the concepts of the decision tree classifier, Please spend some time on how the Decision Tree Classifier works before…
In this article, I will be giving a theoretical explanation about what ensemble learning is and the common types of Ensemble methods.
We regularly come across many game shows on television and you must have noticed an option of “Audience Poll”. Most of the time a contestant goes with the option which has the highest vote from the audience and most of the time they win. We can generalize this in real life as well where taking opinions from a majority of people is much more preferred than the opinion of a single person. …
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