Gold-Price-Prediction-using-Random-Forest-Regressor

Built a Gold Price Prediction tool using Random Forest Regressor from data out of Kaggle

Dataset Source : https://www.kaggle.com/altruistdelhite04/gold-price-data

Regression Methods Used:

Random Forest Regressor is a meta-estimator that fits a set of classification decision trees to different subsamples of a dataset, uses averaging to improve prediction accuracy, and controls overfitting. ... the number of trees in the forest.

What is the difference between a random forest classifier and a regressor?

Random forest classifiers works with data that has individual labels, or data that is well known as a class. Example Patients may or may not have cancer, and people may or may not be eligible for a loan. Random forest regressors have numeric or continuous output and works with data that cannot be defined in a class.