Random Forest Classifier in RapidMiner

In this tutorial, I explain how to build a Random Forest Classifier for the multi-class classification problem. The IRIS data set is utilized. Preprocessing, selecting the target variable, and splitting the data into a training and test set are done. A Random Forest Classifier is then built using the training set and its performance on both the training set and test set are measured. The results are further explained.
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[@siamakroshanzadeh]

Thank you for the tutorial! It was very informative and helpful. I appreciate the detailed explanation of building a Random Forest Classifier using the IRIS dataset. Great work!

[@phessari]

You're very welcome!

[@user-xv5mb1vt2n]

Very informative and engaging. Thank you man!

[@phessari]

no worries

[@MinisterHenry-jc3vk]

can you produce a bot to watch 2 videos on CZcams, convert voice to text. Then consolidate the two videos into one?

[@phessari]

That is a very interesting question. I believe it's feasible but it need some works

[@MinisterHenry-jc3vk]

@@phessari I'm a student at MIT in your class I really hope we can touch on this. Its one of my main objectives to learn how to do this.

[@phessari]

@@MinisterHenry-jc3vk Let me know if you need any help. You can connect with me on LinkedIn www.linkedin.com/in/peyman-hessari/

[@Hiva_13]

سلام