WebbWorked on projects in inventory management, forecasting line stoppages using time series modelling, volume forecasting using macroeconomic indicators like GDP growth rate etc. using techniques like negative binomial regression, used vehicle price calculator based on vehicle and macroeconomic factors using Random forest regression, XGBOOST … WebbAbout. More than 15+ years experience as a Data Scientist/Statistician in Manufacturing, Credit Risk, Transportation, Insurance, Telecommunications, Finance, and Pharmaceuticals. Motivating interest is to apply Data Scientist, Statistical and Optimization techniques to various industries. 1) Time Series Forecasting of Financial Data.
(PDF) Random Forests - ResearchGate
Webb4 nov. 2003 · A new classification and regression tool, Random Forest, is introduced and investigated for predicting a compound's quantitative or categorical biological activity based on a quantitative description of the compound's molecular structure. Random Forest is an ensemble of unpruned classification or regression trees created by using bootstrap … WebbThe book then moves on to other commonly used machine learning tools like linear classifiers such as perceptrons and their generalization, the multilayered counterpart (MLP), Support Vector Machines (SVM), as well as Classification and Regression Trees (CART) and Random Forests. Subsequent chapters focus on linear Bayesian learning ... brain chase coles basingstoke
Random Forest in R – Understand every aspect related to it!
Webb8 nov. 2024 · This article provides an explanation of the random forest algorithm in R, and it also looks at classification, a decision tree example, and more. A Comprehensive Guide to Random Forest in R ... WebbDescription. randomForest implements Breiman's random forest algorithm (based on Breiman and Cutler's original Fortran code) for classification and regression. It can also … WebbFast OpenMP parallel computing of Breiman's random forests for univariate, multivariate, unsupervised, survival, competing risks, class imbalanced classification and quantile regression. Extreme random forests and randomized splitting. Suite of imputation methods for missing data. Fast random forests using subsampling. Confidence regions and … brain chase decoder ring