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: www.igi-global.com/pdf.aspx?t...
Data: github.com/bkrai/R-files-from...
Machine Learning videos: goo.gl/WHHqWP
R code: 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: goo.gl/WHHqWP
Becoming Data Scientist: goo.gl/JWyyQc
Introductory R Videos: goo.gl/NZ55SJ
Deep Learning with TensorFlow: goo.gl/5VtSuC
Image Analysis & Classification: goo.gl/Md3fMi
Text mining: goo.gl/7FJGmd
Data Visualization: goo.gl/Q7Q2A8
Playlist: 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

[@ronithNR]

The best video i have ever seen for a random forest function in R. Thank you so much sir it was very informative, really appreciate your so simple way of explaining all parameters.

[@bkrai]

Thanks for the feedback!

[@joshren7232]

Bharatendra Rai 👍🏽

[@scienceforus8669]

@@bkrai sir, I would like to cite your class. Please let me know the citation information. I truly like your classes. Thank you very much sir

[@ibrahimacoulibaly5199]

The best video I have seen so far regarding explaining Random Forest! Kudo to you, sir!

[@bkrai]

Thanks for comments!

[@jingli8830]

This is the best that I have searched for learning random forest. Thank you for your instructive step-by-step demonstration! Appreciate it a lot!

[@bkrai]

Thanks for comments!

[@atanunow]

Thank you sir ! what a wonderful video!
It help me a lot to understand the subject "Random Forest" and also the application R.

[@thamizhkodi2414]

Truly the best video that explains random forest in detail and clearly with examples

[@bkrai]

Thanks for your comments!

[@siris3957]

Very clear and informative. I learnt so much in just 30 mins.This is so awesome! Please keep doing more of these! Thank you for taking so much effort and making these videos.

[@bkrai]

Thanks for the feedback!

[@victorhenostroza1871]

simplicity brought to the utmost expression so everyone can learn random forests... thanks man

[@bkrai]

Thanks for your comments!

[@MadhuKumarKilli]

One of the best videos on Random Forest in R covering all important functions used in Random Forest.

[@bkrai]

Thanks for comments!

[@amtbutt]

Definitely the best video on random forest. Such a great public service... making video, and sharing code and the data file. THANK YOU!!!!!

[@bkrai]

Thanks!

[@jehangonsal2162]

Excellent work. I really appreciate how you cover everything (from model fitting to visualisation) and break it all down simply. This stuff isn't rocket science, but few instructors convey the beautiful simplicity of Random Forest.

[@bkrai]

Thanks for your feedback!

[@mostafamansour716]

A great video for random forest. I learned a lot from this video compared to any other video I went through in the past. Thank you

[@bkrai]

Thanks for your comments!

[@isaialawaniyasana5209]

Awesome video and very clear explanations, not onlyon how to build a random forest model but also on how to interpret the data, and how to present it.
Thank you for this!

[@bkrai]

You are welcome!

[@dilshadsaeed2857]

Always brilliant professor. Every minute I learn something new with you.

[@bkrai]

Thanks for comments!

[@bluevalley82]

I’ve searched lot of CZcamsr videos about random forest this is the best. Thank you for sharing! God Bless you!

[@bkrai]

You are welcome!

[@anananan3635]

The bestttttt video i have ever seen for a random forest function in R. Thank you so much sir

[@bkrai]

You are most welcome!

[@andresgomez6264]

This is why I love you best teacher out there!

[@bkrai]

Thanks for comments!

[@thuylinhlinh1986]

The best video about random forest so far. Thanks for ur great job! Very helpful!

[@bkrai]

Wow, thanks!

[@googledude5649]

Amazing - thank you very much for your knowledge and your skills of teaching. You seem like a very kind person. I have seen a lot of your videos. Best of luck from Scandinavia to you and your family.

[@bkrai]

Thanks for your thoughtful comments!

[@sherryyu1936]

Thank you sooooo much! I watched too many videos, can't find what I want until finding your video!!

[@bkrai]

Thanks for the feedback!

[@apennyseamstress]

Seriously sir, you just got me through my machine learning final project.
Thank you!!

[@bkrai]

that's great!

[@mahaveerthakur9864]

Nice Videos and very informative. Please Keep sharing the information/Knowledge. Thank you.

[@amitgeneration]

Amazing Sir !! the way you solved and taught Random Forest was impeccable....

[@bkrai]

Glad to hear that

[@myroslavlutsyk5714]

Dear Dr. Rai, I wish sincerely to say you thanks for your clear and patient explanation this method and many other approaches using R. It is easy to understand and to reproduce, and very heplful to plan data analyzing and to analyze the data.

[@bkrai]

Thanks for comments!

[@berend1burg]

Sir I would like to thank you for this great video! Very clear and complete!

[@bkrai]

Thanks for your comments!

[@aman_mashetty5185]

thanks for the video, you cleared my all dought towards the Random Forest tree, thanks for the video & sharing the knowledge

[@bkrai]

Thanks for feedback and comments!

[@flamboyantperson5936]

I'm again watching this video and I would really thank you for such a nice and clear explanation. Please in every video give a theory lecture like this to better understand it's implementation. Thank you so much Sir.

[@bkrai]

Thanks for the feedback!

[@HarmonicaTool]

This is one great video! So concise and so much information and we'll explained. Thank you a lot!

[@bkrai]

Thanks for comments!

[@shaswatamukherjee2888]

Far far better and comprehensive than those paid courses.. you explained so simply yet so much details and clarity in your video. Thank you so much !!

[@bkrai]

Thanks for comments!

[@theaiplayground001]

To the point and concise, thank you

[@manojmishra416]

Thank you so much Dr. Bharatendra Rai ji. I was able to work with the csv file onto Mac now. Really enjoying hands on practice of the same file as instructed in you tube

[@bkrai]

Thanks for the update!

[@whatisthebestplaceto]

Thanks for sharing this video and knowledge. you are explaining it very well and detail. this is the best video.

[@bkrai]

Thanks for feedback!

[@mohit10singh]

Thank you Sir, as others said, I will also echo in their voice that this is the best video in random forest, Please keep making more videos like this, you are doing a great service to all the learners.

[@bkrai]

Thanks for your comments!

[@VenkataDuvvuri]

Excellent video on rf. Thank you

[@chandramanrai9270]

This is an excellent video - comprehensively explained. Thank you, Dr.

[@bkrai]

You are welcome!

[@vinayakbogayyagaru8984]

It is good to learn required things through this video, thanks for such a nice explanation.

[@bkrai]

Thanks for comments!

[@zhaowengu7128]

Thanks a lot! I do appreciated a lot!

[@BrijeshKumar-oi7fc]

This tutorial is Very clear and informative, Thank you for the wonderful video.

[@bkrai]

Thanks for comments!

[@rehab4e2]

thank you very much for a very detail lecture; I think this is the best video I could find about RandomForest

[@bkrai]

You're very welcome!

[@shailajaj9671]

Your teaching is absolutely brilliant. Thanks for sharing your knowledge. I really appreciate it.

[@bkrai]

Thanks for the feedback!

[@bkrai]

Thanks for comments!

[@kapishupadhyay7781]

Excellent , Best so far for Random Forrest

[@bkrai]

Thanks for comments!

[@winnumber101]

What an incredible video... Incredible

[@flyingpama]

Extraordinary video. Thank you so much!!!!

[@bkrai]

Thanks for comments!

[@flamboyantperson5936]

Superb video. Such a beautiful explanation. I really liked your teaching Sir.

[@bkrai]

Thanks!

[@elmoubarkilassad42]

Very clear tutorial on random forest. Thank you.

[@bkrai]

Thanks for comments!

[@dogs4ever1000]

Thanks, very comprehensive video about RF! :)

[@bkrai]

Thanks for comments!

[@meshackamimo1945]

ProfThanks for the best ever videos on statistics n machine learning.
I am one of your ardentfans.
Wouldn't be where I am without your videos...which I have applied in hydrology..
Kindly give us one on hidden Markov chains....hmm.
God bless you.

[@bkrai]

Thanks for comments and suggestion for hidden Markov chains. I'll add it to the list of future videos.

[@mia-jv9cp]

Thank you very much. I learnt a lot about the RF from the video

[@bkrai]

thanks for comments!

[@murrayduncan893]

Thank you for this extremely useful tutorial. Brilliant

[@bkrai]

Thanks for the feedback!

[@PeterJMPuyneers]

Thank you very much for your video. It is very explanatory and I learned a lot from it.

[@bkrai]

Glad to hear that!

[@dishapatel4766]

Ahhhh Thank you so much! This was an amazing video!

[@bkrai]

You're so welcome!

[@velantinavictor1830]

It is a great video Dr. Thanks for clearly explaining.

[@bkrai]

Most welcome!

[@leenanaftal8339]

Excellent tutorial sir… I am new to R and this video helped me a lot in understanding all the steps ,,,,

[@bkrai]

For someone new to R, this link could be a good starting point:
czcams.com/video/s23CMIjfwHk/video.html

[@preetijoshi1437]

Best video on Random Forest

[@bkrai]

Thanks for comments!

[@bshayak]

Great video, thanks for sharing your understanding on RF....

[@bkrai]

Thanks for comments!

[@addisiewubiewassie9243]

Thanks, i am happy if you share videos for prediction as the above is about classification.

[@aphiwemagaya3279]

You should be my lecturer Sir because within 30 min, you were able to simplify something that i couldn't understand in class which took me weeks of research

[@bkrai]

Thanks for comments!

[@haanda47]

Hi Bharat, i don't normally comments on youtube videos, but your explanation on each and every details is excellent. I hope you come up with more videos in R. Thanks a lot.

[@bkrai]

Thanks for your comments! For more R videos you can try following links:
czcams.com/play/PL34t5iLfZddv8tJkZboegN6tmyh2-zr_T.html
czcams.com/play/PL34t5iLfZddu8M0jd7pjSVUjvjBOBdYZ1.html

[@110220V]

Thank you for this excellent walk through.

[@bkrai]

Thanks for comments!

[@MAbdullah47]

Thank You for this nice tutorial

[@gaykarsamir]

thanks a lot for this video..very useful..keep the good work going :)

[@mukhtaradamuabubakar370]

It was very useful and signifcant to my research! Thanks.

[@bkrai]

You are welcome!

[@siyuanmeng443]

Thank you very much for the video, you made everything clear and easy.

[@bkrai]

You are very welcome!

[@InfinitesimallyInfinite]

Brilliant. I love your work.

[@bkrai]

Thanks for comments!

[@StarLakeFarm]

Most excellent video!!!

[@wirantoaji6079]

so clear explanation and easy to understand. thanks!

[@bkrai]

Great to hear!

[@Workuj]

Thanks Rai so helpful)

[@mariaa1074]

Really clear and useful tutorial ! Thank you.

[@bkrai]

Thanks for comments!

[@deniseye8382]

Clear explanation, easy to follow. Thanks a lot!

[@bkrai]

Thanks for the comments!

[@nitinkumar-zk9wh]

I like your explanation.

[@jalluravikiran4146]

thank you sir.. excellent video

[@sachinrathi7814]

Undoubtedly Awesome Stuff

[@bkrai]

Thanks for comments!

[@victorhenostroza1871]

Sir, really, u r the man. thank you.

[@bkrai]

Welcome!

[@FPrimeHD1618]

You have the best damn video's. You are so thorough and I love that you don't use easy data sets.

[@bkrai]

Thanks for comments and feedback!

[@FPrimeHD1618]

@@bkrai Absolutely! This may be asking a lot, but it would be really nice to see your spin on the Titanic Kaggle data set.

[@bkrai]

I'm adding it to my list of future items. Thanks

[@FPrimeHD1618]

@@bkrai Awesome! I super excited. I have almost done every classification ML algorithm for the data set. But, I know there is massive room for improvement. Feature engineering was a very interesting process. I am a data analyst by trade, but I have never gone to this extent of creating features. Most of our features are already well defined within our business model.

[@bkrai]

Thanks!

[@venkkandadai6042]

Great video. Your video in CART was also excellent

[@bkrai]

Thanks!

[@venkkandadai6042]

are you available for consulting?

[@meetraj07]

You have explain this very nicely. Very good video.

[@bkrai]

Thanks for comments!

[@leonardohernandez9804]

Man, you are probably the best dude when it comes to R. You should consider teaching R courses on Udemy. Or come teach in NYC!

[@bkrai]

Thanks for your comments!

[@NishantYadav-kz4es]

Thanks for the knowledge

[@bkrai]

Thanks for comments!

[@felipe_zune]

Hello Dr. Bharatendra... Thanks for you video

[@bkrai]

You are welcome!

[@andreasmith4124]

This was awesome. Thank you!!!

[@bkrai]

thanks for comments!

[@xialinzou2110]

Best tutorial Video for Random Forest in R so far! Thank you Mr. Rai. And I have one more question---I'm trying to predict the Player of the Week (NBA) based on the historical data. Given that the NBA select POW weekly based on the player's stats of that week compared to others, how should I deal with the data.For example, I have all 88 weeks dataset for all players, how should decide the which part the TRAIN/TEST data is? I can't just combine them together, can I?

[@gmkjmi]

Very good Video...keep it up thanks for sharing with us.

[@bkrai]

Thanks for comments!

[@shakiulislam6883]

Thank you so much sir! it was super helpful

[@bkrai]

You are welcome!

[@ikramabdelkhalek7543]

Thank you very much for this amazing so helpful video (y)

[@bkrai]

Thanks for feedback!

[@asterlookanalytics9853]

The best video on random forest in R: there is also one on Artificial Neural Network, glm by the same person

[@bkrai]

Thanks for comments!

[@asterlookanalytics9853]

I am also using the methods after these tutorials

[@selamawitdamtew3583]

Thank you very much for giving all the clarity regarding Random Forest.
Can you also give a little bit of explanation on how to analyze spatial data? Thank you in advance!

[@bkrai]

I've added analysis of spatial data to list of future videos. Thanks!

[@nivedyaashokan1863]

Great video! Thanks!

[@bkrai]

Thanks for comments

[@manuelgoncalves9753]

Great video, thank you!

[@bkrai]

My pleasure!

[@sovon08]

This is the best video!!

[@bkrai]

Thanks for comments!

[@hans4223]

First class, awesome :)

[@bkrai]

Thanks for comments!

[@hans4223]

Dear sir,
Please advise on below request -
I think ROSE package work for binary classification and doesn't work for multi-class classification. How to do for this multi class classification ?
Can you please upload a video for detailed data manipulation from raw data to ready data to process .
Again thanks for great support.
Regards,
Hanspal Yadav

[@bkrai]

I would suggest you do 2 at a time.

[@hans4223]

Respected Sir,
I am getting below error while trying to execute "over sampling" in CTG data for multiclass prediction of NSP -
code Over

[@thebible913]

Great video very very very good
Thank you so much

[@bkrai]

Thanks for comments!

[@kartiksrikumar6069]

Awesome; thank you!

[@bkrai]

Thanks for comments!

[@desertrose00]

quality video.

[@lilianmariawiens4781]

Magnificent video

[@bkrai]

Thanks!

[@yogurtunnghe]

Great video, you made random forest clear and easy to understand. Thanks a lot. Would you please make an example on partial least square regression for discrimination and prediction?

[@bkrai]

Will plan it for future. Thanks!

[@alia.moazzami2983]

Great thanks for informative video

[@bkrai]

Thanks for comments!

[@semartshirt2492]

very informative sir !

[@bkrai]

Thanks for comments!

[@alesandraaraujodesouza9811]

You're the best!!!!!!

[@bkrai]

Thanks for comments!

[@californiandonagriga4509]

Great video!

[@bkrai]

Thx!

[@Nil_money]

Very nicely explained.

[@bkrai]

thanks for comments!

[@sapnavalsa7932]

Amazing video sir...learn a lot

[@bkrai]

Glad to hear that