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Random Forest in R - Classification and Prediction Example with Definition & Steps

Provides steps for applying random forest to do classification and prediction. Research article on random forest: https://www.igi-global.com/pdf.aspx?t... Data: https://github.com/bkrai/R-files-from... Machine Learning videos: https://goo.gl/WHHqWP R code: https://github.com/bkrai/Top-10-Machi... For citation as reference in a research paper, use following: Meshram, A., and Rai, B. (2019). “User-Independent Detection for Freezing of Gait in Parkinson’s Disease Using Random Forest Classification,” International Journal of Big Data and Analytics in Healthcare, Vol. 4, Issue 1, 57-72. Rai BK (2017) “Feature Selection and Predictive Modeling of Housing Data Using Random Forest,” International Journal of Social, Behavioral, Educational, Economic, Business and Industrial Engineering, Vol. 11, No. 4, 880-884. Xiaoling, Lu., Rai, B., Yan, Z., and Li, Y. (2018). “Cluster-based Smartphone Predictive Analytics for Application Usage and Next Location Prediction,” International Journal of Business Intelligence Research, Vol. 9, No. 2, 64-80. Rai BK, (2020). “Supervised Machine Learning: Application Example Using Random Forest in R,” chapter in book titled Mathematics Applied to Engineering and Management, edited by Mangey Ram and S. B. Singh, CRC Press Taylor & Francis Company. Topics 00:00 CTG data description 01:58 Data partition 03:04 What is a random forest classification model? How it work? Why and when to use? 08:16 Random forest in R 10:51 Prediction & confusion matrix - train data, caret package, accuracy, sensitivity & interpretation 16:27 Prediction and confusion matrix with test data 17:33 Error rate of random forest, bootstrap samples and out of bag (oob) error 18:04 Tune random forest model 22:25 Number of nodes for trees 23:33 Variable importance 27:04 Partial dependence plot 28:31 Extract single tree from the forest 29:38 Multi-dimensional scaling plot of proximity matrix random forest is an important tool related to analyzing big data or working in data science field. Machine Learning videos: https://goo.gl/WHHqWP Becoming Data Scientist: https://goo.gl/JWyyQc Introductory R Videos: https://goo.gl/NZ55SJ Deep Learning with TensorFlow: https://goo.gl/5VtSuC Image Analysis & Classification: https://goo.gl/Md3fMi Text mining: https://goo.gl/7FJGmd Data Visualization: https://goo.gl/Q7Q2A8 Playlist: https://goo.gl/iwbhnE R is a free software environment for statistical computing and graphics, and is widely used by both academia and industry. R software works on both Windows and Mac-OS. It was ranked no. 1 in a KDnuggets poll on top languages for analytics, data mining, and data science. RStudio is a user friendly environment for R that has become popular. #RandomForest #RandomForestAlgorithm #RandomForestClassification #MachineLearning #RProgramming #MachineLearningTutorial #MachineLearningCourse #MachineLearningAlgorithm