Random forests or random decision forests is an ensemble learning method for classification, regression and other tasks that operates by constructing a multitude of decision trees at training time. This repository depicts sequential implementation of Random Forest Classifier, feeturing engineering for selecting, manipulating, and transforming raw data into features that can be used in supervised learning.
Obtained accuracy - 97.68%