Machine Learning Tutorial Python - 11 Random Forest

Random forest is a popular regression and classification algorithm. In this tutorial we will see how it works for classification problem in machine learning. It uses decision tree underneath and forms multiple trees and eventually takes majority vote out of it. We will go over some theory first and then solve digits classification problem using sklearn RandomForestClassifier. In the end we have an exercise for you to solve.

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Exercise: Exercise description is avialable in above notebook towards the end

Topics that are covered in this Video:
0:00 Random forest algorithm
0:50 How to build multiple decision trees based on single data set?
2:34 Use of sklearn digits data set to make a classification using random forest
3:04 Coding (Start) (Use sklearn digits dataset for classification using random forest)
12:04 Exercise (Classify iris flower using sklearn iris flower dataset and random forest classifier)

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#️⃣ Social Media #️⃣

[sanchit]

Keeping the tutorial part aside (which is great), I really love your sense of humor and it's an amazing way to make the video more engaging. Kudos!!
Also, thank you so much for imparting such great knowledge for free.

[zerostudy]

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I am just a humble python hobbies who took local course yet still I don't understand most of the lecturer says. Because this channel i've finally found fun with python. In just 2 weeks(more) I already this Level? Man....! Can't Wait for Neural Network but only from this channel

[panagiotisgoulas]

It is a good practice to make a for loop for the n_estimators check the score for one of these:

scores=[ ]
n_estimators=range(1, 51) #example
for i in n_estimators :

model.fit(X_train, y_train)
scores.append(model.score(X_test, y_test))
print('score:{}, n_estimator:{}'.format(scores[i-1], i))

plt.plot(n_estimators, scores)
plt.xlabel('n_estimators')
plt.ylabel(('testing accuracy')

And then you can sort of see what's going on. This practice is very useful for knearest neighbors technique for calculating k.

[adityahpatel]

I cannot quite express how amazing teaching you are doing. I am doing masters one of the finest universities in America and this is better than the supervised learning class I am taking there. Kudos! Please keep it up. appreciate you are making this available for free although I would be willing to see your lectures even for a fee.

[roodrakanwar]

I achieved an accuracy of .9736. Earlier, I got an accuracy of .9 when the test size was 0.2 and changing the number of trees wasn't changing the accuracy much. So, I tweaked the test size to .25 and tried different number of tree size. The best I got was .9736 with n_estimators = 60 and criterion = entropy gives a better result.
Thank you so much sir for the series. This is the best Youtube Series on Machine Learning out there!!

[chrismagee]

FYI if you are using version 0.22 or later the default value of n_estimators changed from 10 to 100 in 0.22

[srujanjayraj]

The way you teach or explain the concepts completely different thanks a Please make more videos

[Tuoc_Nguyen]

For Iris Datasets I got score =1 for n_estimators = 40, 50, 60
Thank sir very much

[kausikkar]

Sir, I am damn impressed by you!!!! You are the best ML instructor here on YT!!!!

[pablu_]

Thank you Sir for this awesome Explanation about RandomForestClassifier . I got score of 1.0 for every increased value in n_estimators

[abhinavsharma]

I got an accuracy of 0.982579 by giving, n_estimators = 100, well 100 is the default value now, and sir, big fan of your teaching 🙂

[Pacificatorrr]

You sir, are a gem! Thank you for this series!

I managed to get an accuracy of 98%!

[motox]

Great Video! I'm working on my first project using machine learning and am learning so much from your videos!

[devendragohare]

I Got 100% accuracy!.... by changing criterion = "entropy"

[tanishqrastogi]

ok so i read one comment and put test_size = 0.25 and n_estimator = 60. I rerun my test sample cell as well as model.fit and model.predict cell and got the accuracy of 100%. I am having a god complex right now thank you for this amazing series

[AbhishekSingh-ogkf]

I can watch this type of videos whole day without take any break. Thank you!!!

[sumitkumarsain]

Just love ur videos. I was struggling with python. With ur videos was able to get everything in a weeks time. Also completed pandas and bumpy series. I would highly encourage u to start a machine learning course with some real life projects

[VivekKumar-lixr]

Hello Sir, I have started learning pandas and ML from your channel, and i am amazed the way you are teaching.
For Iris Datasets I got score =1 for n_estimators = 30

[geethanjaliravichandhran]

Hi sir, i did your exercise of iris data and got an accuracy of 1.0 with n_estimators=80

[rameshthamizhselvan]

frankly telling your videos are more neat and clear than anyother videos in the youtube