Implementing Random Forest In Python|How to Implement Random Forest In Python|Random Forest ML

Implementing Random Forest In Python|How to Implement Random Forest In Python|Random Forest ML
#RandomForestInPython #UnfoldDataScience
HI,
My name is Aman and I am a Data Scientist.

About this video:
Want to learn why Random Forests are one of the most popular and most powerful supervised Machine Learning algorithm in Machine Learning? What this video tutorial explaining the basics of Random Forests.
Random forest algorithm is a one of the most popular and most powerful supervised Machine Learning algorithm in Machine Learning that is capable of performing both regression and classification tasks. As the name suggest, this algorithm creates the forest with a number of decision trees.
In general, the more trees in the forest the more robust the prediction. In the same way in the random forest classifier, the higher the number of trees in the forest gives the high accuracy results.
In this video, I am going to show how to implement Random forest in python. Below questions are answered in this video:
1. How to implement random forest in python
2.How to tune optimal parameters in random forest
3 How to improve performance of random forest model
4.How to choose optimal parameters in random forest

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[hanas.]

Very nice video, just a small hint. Avoid naming the data "train" as it can be easily confused with train/test code, especially for beginners

[himanshudhakecha]

good video - but at the end of the video if you discuss the result and insight it make it more meaningful.

[marcellinusokoh]

It's a great one here... I am working using random forest to predict stock prices.. I need a heads up

[anantharamaniyer]

Thanks for the time taken to make this and the clarity of explanation. In your approach, have you considered the 'missing-ness' of the features before choosing to use mode(). For example I have a dataset with a couple of categorical variables which have 'Nan' in them. They can be classified as MCAR and when reading through various articles people adopt either your approach or go further to estimate the 'Nan' using a prediction such as OneHot encoder / Label Encoder or kNN. Have you also done something similar ?

[abhishekgautam]

Technical concepts explained in crystal clear way. Awesome!

[harshpathak]

Can you explain why we had to dumify the object data ?? Thanks for the video.

[subinoymaity]

Can you help me how to use random forest classifiers and support vector machines in mineral exploration... your little bit helps give me confidence

[kandiahchandrakumaran]

Good work, Thank you.
Have you released video on Time_Event, survival analysis using Random Survival Forest Model, because of censored data? I so where can I find? If not are you able to create and upload>
Best wishes,
Chandra

[adwinraj]

Hi, from the code above the n_estimator parameter you use around 9 value ..how about if I decide to use max.depth ..example max_depth [24] is this correct ? Still beginner to this

[sakshidubey]

Sir my target output which I am using for prediction is a three category eg yes, no, maybe what modification shld we do

[pxofbig]

I’m trying to analyse effects of factors on my response variable…can i use random forest or is it only for prediction?

[phanikumar]

Hi aman, in the train test split u considers input as train and label as output and in the train u haven't removed the survived column and considerd survived in both the input and

So can u plz clarify it.. I like the way u deliver the content 🙏

[animatrix]

Sir i would reqest you to go a bit in depth about the concepts

[GauravDhage]

Which optimization technique used for training in random forest?

[rajdipr]

Thanx Aman for this nice video...I've a question...what is the intuition in replacing the null values of Cabin with .mode()[0]...the o/p of df['Cabin'].mode() is follows

0 B96 B98
1 C23 C25 C27
2 G6
dtype: object

[rajeshkannan]

"Description, title, bullet_points " are 3 out of 5 features in my dataset, which are string datatype with special characters in it, there are some NULL values in the features, how to fill that NULL values and what type of encoder should i use before train my ML model.
FYI :
Other two features are " Product_ID, Product_Type_ID", output of my dataset is " Product length"

[kshamahirekhan]

amazing explanation, , thank you so much.

[awanishkumar]

hey Aman as you used one parameter n_estimator, can you please show how to use other parameters like class_weight, max_features, criterion, max_leaf, max_depth, , kindly reply . atleast hint or give some tips ..

[sanjaygiri]

I am getting this ValueError : multiclass format is not supported . Can u explain why?

[dasgupts]

if we use rf.predict.proba instead of rf.predict do we need to caliberate it to get the actual probabilities or we can use predict.proba probabilities?