Couple of days back, when I was in one of the events, I came across a very interesting question - someone asked me - " why Random Forest Algorithm is so popular amongst all algorithms"
I started answering saying, if I talk about me - the ML algorithm which gives me better accuracy and less overfitting is best for me. Also it depends on type of business problem statement I am working, approach I want to follow supervised or unsupervised, and so on. The trend keeps changing I have seen - where people were talking only about Logistic Algorithm, then XGBoost, then GAN then something ... then Random Forest....so on. It depends upon what you are looking for.
So I started seeing what people has to say about it. And found multiple blogs -
Somewhere I found that it fails too or it has some disadvantages associated-
So, every algorithm might come with pros and cons. It is more important to see, what your data is about?, what you are trying to predict, what would be the best model - which has low overfitting, good predictions or may be easy to interpret. It lot more takes in understanding data, making data clean and pre process to bring it in a required shape [matrix] to do better data modeling. Rest is everyone's choice which algorithm to choose.
What do you think? I would like to learn - Does random forest is your favorite algorithm too, If yes, then why and if No then too why? I would like to hear your insights. So, please do write me at instagram @dataneighbor or website www.vaishalilambe.com or simply comment on LinkedIn / Facebook / Youtube channel. I am eager to know, your favorite algorithm too.
If anyone doesn't know Random Forest Algorithm, you can simple visit my website for blog
or watch my videos on instagram, Youtube or Faceboook page, or check my Github repository code. Links are as below -
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See you on Thursday! Stay Tuned!!