Do Random Forests work better than Multinomial Logistic Regression for Prediction of Categorical Non-Binary Variables? Why? In the previous question was suggested that Multinomial Logistic …

Jan 5, 2017 · This page discusses the choice between Random Forest regressor and classifier, explaining their differences and when to use each.

Mar 28, 2018 · I understand that the probability in the random forest algorithm uses the count of trees that vote for a certain class, while logistic regression uses MLE. What are the implications of using …

Jan 9, 2019 · Why Don't we use Random Forest always in place of Linear or Logistic Regressions. When will Linear and Logistic out perform Random Forest.

Jan 6, 2020 · Logistic regression to be picked in case we want to advise the impact on y variable on what change on any x variable. Random forest works good on mixed data and very effective for …

Oct 30, 2022 · Yes, a model like a random forest allows much more flexibility in the modeling than a vanilla logistic regression, but this runs the risk of fitting the model to coincidences in your data …

Feb 26, 2017 · " The fundamental difference between bagging and random forest is that in Random forests, only a subset of features are selected at random out of the total and the best split feature …

Feb 15, 2018 · Logistic regression vs Random forest vs GBM: equal performance? Ask Question Asked 7 years, 9 months ago Modified 7 years, 5 months ago

May 28, 2021 · The Random forest method is an ensemble method that consists of multiple decision trees and is used for both regression and classification. A decision tree is a very simple technique …

Feb 27, 2022 · I chose to use logistic regression to analyze both models. I am not familiar with random forest models, so I wanted to make sure my reasoning for choosing logistic regression over random …