Artificial Intelligence for Big Data

Random Forest

Random Forest is the class of algorithms that comes under the supervised learning algorithm category. It is based on forests of trees, which is similar to decision trees in certain contexts. Random Forest algorithms can be used for both classification and regression problems. A decision tree gives the set of rules that are used in building models, which can be executed against a test dataset for the prediction. In decision trees, we first calculate the root node. To calculate the root node, we use information gain. For example, if you want to predict whether your friend will accept a job offer or not. You need to feed the training dataset of the offers they have accepted to the decision tree. Based on this, the decision tree ...