tulika  goyal tulika goyal

In the next article, we will solve the same problem using a random forest algorithm. We hope that random forest will be able to make even better prediction for these borderline cases. But, we can never generalize the order of predictive power among a CART and a random forest, or rather any predictive algorithm. The reason being every model has its own strength. Random forest generally tends to have a very high accuracy on the training population, because it uses many different characteristics to make a prediction. But, because of the same reason, it sometimes over fits the model on the data. We will see these observations graphically in the next article and talk in more details on scenarios where random forest or CART comes out to be a better predictive model.

tulika  goyal

tulika goyal Creator

B-tech 2nd year student of polymer science.

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tulika  goyal