What kind of data is Random Forest good for? June 15, 2022 Random forests is great with high dimensional data since we are working with subsets of data. It is faster to train than decision trees… Continue Reading
What is random forest good for? June 15, 2022 Random forest can be used on both regression tasks (predict continuous outputs, such as price) or classification tasks (predict categorical or discrete outputs). Click… Continue Reading
Does Random Forest reduce dimensionality? June 15, 2022 Linear Discriminant Analysis, or LDA, is a multi-class classification algorithm that can be used for dimensionality reduction. Click to see full answer Can decision… Continue Reading
How does random forest improve upon bagging? June 15, 2022 Random Forests are an improvement over bagged decision trees. A problem with decision trees like CART is that they are greedy. They choose which… Continue Reading
What is the benefit of removing redundant examples from the training set? June 15, 2022 Hence irrelevant and redundant data should be removed from training data sets to improve the predictive speed, reduce the time taken to build the… Continue Reading
Why is XGBoost better than LightGBM? June 15, 2022 The advantages are as follows: Faster training speed and accuracy resulting from LightGBM being a histogram-based algorithm that performs bucketing of values (also requires… Continue Reading
Are Random Forests always better than decision trees? June 15, 2022 Random forests is great with high dimensional data since we are working with subsets of data. It is faster to train than decision trees… Continue Reading
Can we use XGBoost with random forest? June 14, 2022 Key Difference Between Random Forest vs XGBoost Random Forest and XGBoost are decision tree algorithms where the training data is taken in a different… Continue Reading