Decision Tree Algorithm | Decision Tree in Python | Machine Learning Algorithms | Edureka

🔥 Machine Learning with Python (Use Code "𝐘𝐎𝐔𝐓𝐔𝐁𝐄𝟐𝟎") : www.edureka.co...
This Edureka video on Decision Tree Algorithm in Python will take you through the fundamentals of decision tree machine learning algorithm concepts and its demo in Python. Below are the topics covered in this tutorial:
1. What is Classification?
2. Types of Classification
3. Classification Use Case
4. What is Decision Tree?
5. Decision Tree Terminology
6. Visualizing a Decision Tree
7 Writing a Decision Tree Classifier fro Scratch in Python using CART Algorithm
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#decisiontree #decisiontreepython #machinelearningalgorithms
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About the Course
Edureka’s Machine Learning Course using Python is designed to make you grab the concepts of Machine Learning. The Machine Learning training will provide deep understanding of Machine Learning and its mechanism. As a Data Scientist, you will be learning the importance of Machine Learning and its implementation in python programming language. Furthermore, you will be taught Reinforcement Learning which in turn is an important aspect of Artificial Intelligence. You will be able to automate real life scenarios using Machine Learning Algorithms. Towards the end of the course, we will be discussing various practical use cases of Machine Learning in python programming language to enhance your learning experience.
After completing this Machine Learning Certification Training using Python, you should be able to:
Gain insight into the 'Roles' played by a Machine Learning Engineer
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Describe Machine Learning
Work with real-time data
Learn tools and techniques for predictive modeling
Discuss Machine Learning algorithms and their implementation
Validate Machine Learning algorithms
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Why learn Machine Learning with Python?
Data Science is a set of techniques that enables the computers to learn the desired behavior from data without explicitly being programmed. It employs techniques and theories drawn from many fields within the broad areas of mathematics, statistics, information science, and computer science. This course exposes you to different classes of machine learning algorithms like supervised, unsupervised and reinforcement algorithms. This course imparts you the necessary skills like data pre-processing, dimensional reduction, model evaluation and also exposes you to different machine learning algorithms like regression, clustering, decision trees, random forest, Naive Bayes and Q-Learning.
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[@edurekaIN]

Got a question on the topic? Please share it in the comment section below and our experts will answer it for you. For Edureka Python Machine Learning Course curriculum, Visit our Website: bit.ly/2OpzQWw

[@vigneshviki4955]

code explanation should be slow as it is a key area just moving ver fast

[@monuvishwakarma8133]

How did you decided the position of windy and humidity?

[@YemiAdelaiye]

I HAVE A QUESTION: Why was the temperature feature totally ignored in the dataset while building the decision tree? While Outlook, Humidity and Windy were all chosen.

[@hammadkhan7927]

I think it is best video for decision tree. Can you please give me the notes that you used to teach.

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We are glad to have learners like you. Please do share your mail id so that we can send the notes or source codes. Do subscribe our channel and hit that bell icon to never miss an video from our channel

[@syammangineni5857]

Excellent teaching, great explanation. Thank you sir.

[@mustafabohra2070]

Best tutorial on KZbin!

[@YemiAdelaiye]

Thank you! I have been looking for a video all week that would break "decision tree" down for me. This is it!

[@edurekaIN]

We are very glad to hear that your a learning well with our contents :) continue to learn with us and don't forget to subscribe our channel so that you don't miss any updates !

[@abhishekjani8695]

CART Algorithm uses Gini Index but you have implemented the dataset using entropy and Information gain so it will not be ID3 Algorithm?

[@kainatanjum7991]

Thank you for making it clear and concise, additionally can you please provide the source code ?

[@edurekaIN]

We are glad to have learners like you. Please do share your mail id so that we can send the notes or source codes. Do subscribe our channel and hit that bell icon to never miss an video from our channel

[@gidinated]

thank you for the clear explanation!

[@edurekaIN]

You are welcome :) Glad it was helpful!

[@jainharshal3088]

very well explained the math behind the decision tree. thank you

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[@gamingengine5987]

Great Explanation!! Thank You

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[@manivarmaindukuri7801]

Sir , I was assigned a project on fraud detection . Which algorithms should I learn to train many transactions and detect if a transaction is legitimate or fraud ? I wanted to implement in Python . Please guide me in this project .

[@edurekaIN]

Hey Manivarma, Classification and clustering algorithms are good for fraud detection and anomoly detection. So algorithms like, SVM, KNN, K-Means, Decison trees, Random forest are relevant. Hope this helps!

[@rishird5635]

The code is not there in the description .. can you get me that? The video lecture was awesome.. I tried doing alongside..but have some errors. If given the sample code may be I can check it out. Cheers

[@edurekaIN]

Hey Rishi, thank you for watching our video. We are glad that you liked our content. Sure, mention your email address and we will share it with you. Cheers :)

[@sarojbodepudi4941]

This lecture was exactly hitting on the nail, this helped in clarifying my doubts. Is it possible to share the link for this python code, that could be very helpful! Thanks

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Please share your email id with us (it will not be published). We will forward the code to your email address.

[@quamar0313]

Thanks for great explanation

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[@sarangabbasi2560]

WOW great work

[@PritishMishra]

Good teaching and animation......

[@mahfuzulhaquenayeem8561]

Thank you a lot for creating this for a beginner like me.

[@edurekaIN]

You're welcome 😊 Glad you liked it!! Keep learning with us

[@sankettakle9980]

hey great explanation .. covered all the topics neccesaary could you please share the code

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Thank you. Please share your email id with us (it will not be published). We will forward the code to your email address.

[@silasvick]

Am building a model to predict a likelihood that someone may commit suicide.. Can i use this algorithm?

[@edurekaIN]

Hi there, this probably depends on the kind of data you have collected. If you have good labelled datasets which can help you understand the persons mental state then this algorithm would definitely work. But if it is something where your dataset is broken and not complete and you cannot predict any reason which causes the suicide, then unsupervised algorithms will work. Hope that is helpful.

[@STTPwithRajani]

Crystal clear 🙂 thanks 🙏

[@edurekaIN]

You are welcome 😊 Glad it was helpful!!

[@vithikapungliya6043]

Best video!

[@hafzatinnurlatifa2589]

thank you, it's really helpful

[@edurekaIN]

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[@azharali1932]

Hi Sir, Please share the link to the code that you have explained above. Thanks.

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[@jaber4474]

very informative video I really need to learn more about Machine Learning in Python I wish that you post more videos in that useful and interesting topic. Like d this video , Thank you

[@edurekaIN]

Hey Jaber! Thank you for appreciating our efforts. You can check out our Complete Machine learning tutorial here: kzbin.info/www/bejne/mGPUZoJ8qd2gbKM Hope this is helpful. Cheers!

[@pratheekhebbar2677]

what an explanation.simply superb sir .so simple and easily you explained

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[@komalrathod7746]

Thank you for the explanation. Can you please share the code?

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[@Jokesterzone5677]

Satisfactory explanation among all resources.... 10 out of 10

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[@omkarparab8780]

Well explained !! got a high level overview , for intuitive understanding of few terms referred google . All in all thankyou for this vid just one correction at 30:15 one entropy should of rainy but both are written as sunny.

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[@aritrasaha1091]

Excellent session . Is it possible to provide the python codes ?

[@PradipDas-og8yx]

Thankyou, you made it clear. Could you please share the code?

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[@ML-uy8bs]

its really awsm........ very helpful...

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[@skywalker66ful]

Very Nicely Explained .. Thanks ..

[@qizhang5885]

Very clear explain. May I have the source code?

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[@RajChauhan-hd9hu]

If the training_data is huge then how can we make the necessary changes and get the same correct output?

[@edurekaIN]

Hey Raj, You can set the variable to r rangle. For example, if you have around 5000 tuples, then you can use just 200 tuples and then assign it to train data. After that you can use the algorithm and test the data based on the chosen tuples

[@surender6320]

Hi, This is Surender, great explanation, can you please provide the python code.

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Thank you. Please share your email id with us (it will not be published). We will forward the code to your email address.

[@indrajitmukherjee5964]

Awesome video guys. one small request can I get the demo code used here for my practice ?

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Hey Indrajit! We are glad you loved the video. Please do mention your email ID over here and we will send the files to you. Cheers!

[@anthonyfernandez894]

Absolutely stunning, very well explained, clear ideas, awesome stuff & remarkable cases...substantial learning at high level. Thanks & regards from Costa Rica.

[@jackyhuang6034]

Awesome video. May I have the code that was used at the end of the tutorial? Thanks in advanced.

[@edurekaIN]

Thanks for the compliment! Please share your email id with us (it will not be published). We will forward the code to your email address.

[@priyanshvatsal9791]

Awesome explanation

[@sumahullur5138]

great video! You made it simple and clear, thank you so much

[@vishwanathravula9239]

Hi, Could you guys give me some guidance to implement the decision tree algorithm in torch7 using Lua.

[@edurekaIN]

Hey Vishwanath, "indico.cern.ch/event/472305/contributions/1982360/attachments/1224979/1792797/ESIPAP_MVA160208-BDT.pdf This might be useful to you. Cheers!"

[@codeindia4730]

Kindly . Correct The thing On timestamp 28:42 The last Entropy calculation should be of rainy but taken of sunny again.

[@adhithyarajan2311]

What is decision tree with relearning of nodes?

[@karthikarg]

Why didn't 'temperature' come into picture while constructing the decision tree? Is it because the information gain is least compared to all other nodes? if yes, then every time when we construct the decision tree should we ignore the parameter with least info gain?

[@edurekaIN]

Hey, You are correct, it is because it is the least compared element. Not that you should always ignore it but it depends on the use case.

[@datasciencecamp]

The code and data is not available in description. Please share the link.

[@edurekaIN]

Please share your email id with us (it will not be published). We will forward the code and dataset to your email address.

[@rimpinag6346]

Really great explanation ... awsome video ... i understand very clearly and like it🥰

[@asmaalaila9337]

Thx .it's great

[@EngineersLife-Vlog]

Anyone with no prerequisites will able to understand Edureka all classes.

[@edurekaIN]

Hey Souman, that is our aim. Thank you for appreciating our efforts! Keep supporting us, cheers :)

[@atharvav]

Right, Alright!

[@suhasnayak4704]

What are computational complexity for Decision Tree? Can you please give analysis for tree training phase and prediction phase please.

[@MrGeorgerocker]

Hey, great video but I have a question i am working with a data set that has 569 instances and 30 variables, problem is that the variables aren't like the example, they are not standard options, like shown in the video where outlook has 3 distinct options, these variables are all doubles, they range from 7.33 up to 22.45 or something like that, so i'm really not sure how to calculate entropy for that

[@edurekaIN]

Hey, Entropy is straightfoward and really simple to calculate. Can you elaborate?

[@SnehaKondapalli]

hi could you please share the ppt material and code used in this video. This is very helpful for my assignment

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[@salehaali1185]

Thanks alot for the wonderful video. kindly share the code plz asap.

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Please share your email id with us (it will not be published). We will forward the code to your email address.

[@simhanarasimha386]

Nice explanation. Could you please share the code, it would be helpful, Many thanks in Advance!

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Thank you. Please share your email id with us (it will not be published). We will forward the code to your email address.

[@nchsrimannarayanaiyengar8003]

wonderful

[@shareInfo2023]

very nice explanation sir .........Great Thanks to You...

[@edurekaIN]

Hey Ram, glad you loved the video. Do subscribe and hit the bell icon to never miss an update from us in the future. Cheers!

[@zuoweizhu1797]

Nice tutorial， Decision Tree well explained

[@sarangabbasi2560]

Can u provide practice problems with solution.

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[@jayedakbar2425]

Thanks for the great video. Can i have the code please?

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[@UttamKumar-sc1gw]

Great Video . Thanks much.

[@shagunsrivastava5837]

hi!! could you please share the link to python code explained in the video??

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Please share your email id with us (it will not be published). We will forward the code to your email address.

[@এসোশিখিসহজে]

great explanation..may i have the code

[@edurekaIN]

Thanks Obaid. Please share your email address, we will send you the code.

[@Raj64395]

Excellent explanation

[@talharasheed5322]

Very helpful, really obliged of edureka 🙏

[@jaikishangupta1824]

Can anyone tell how windy child decided to strong and or weak and how its value is true and false also decided?

[@hariharancse7273]

How to use decision tree cart algorithm in various problems sir! I am develop the project of"projector control" in supervised programming can I create??

[@edurekaIN]

Hey! Yes, You definitely can create.

[@hafizibtisam]

sir can i get code of it?

[@edurekaIN]

Please share your email id with us (it will not be published). We will forward the source code to your email address.

[@paruljoshi7648]

Hello, Thanks a lot for this tutorial...can I get the code please? as I'm facing few errors while running it like I Got the error that Question takes no argument. Please share the code.

[@edurekaIN]

Hi Parul, we do provide practice codes to enhance your learning experience, kindly drop in your email id to help us assist you with it. Cheers :)

[@ashwatsharma7511]

Very Well explained ..👍 Can I get code file??

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Hi Ashwat, kindly drop in your email id to help us assist you with the required source codes. Cheers :)

[@mahadihasan-yi5pz]

great help for me. could I get the code?

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[@keerthikeethika9551]

hii sir...nice video please share the source code and dataset

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[@maldito21st]

Very informative video. Can you share the code as our reference? Thanks.

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[@santoshbirje2705]

very clear. Thank you so much :)

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Hey Santosh, we are glad you loved the video. Do subscribe to the channel and hit the bell icon to never miss an update from us in the future. Cheers!

[@AshishPatel-kn3kc]

its really awesome explanation. As usual.

[@pragatisrivastava4872]

Nice video, may i have the code that was used at the end of the video.

[@edurekaIN]

Thank you. Please share your email id with us (it will not be published). We will forward the source code to your email address.

[@omkarparab8780]

Can I get the code ? I couldnt find in the description

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[@nuraisyah9509]

what did you import for doing tree decision?

[@edurekaIN]

Hi Nur, You have to first import the required libraries and datasets. Hope this helps.

[@davidcecil1477]

Can I please get the entire source code to review please? It'd be of great help!

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We are happy that Edureka is helping you learn better ! We are happy to have learners like you :) Please share your mail id to share the data sheets :) Do subscribe the channel for more updates : ) Hit the bell icon to never miss an update from our channel : )

[@huhwhat8831]

Great video. But could you please provide the source code. It will be helpful for us to study it.

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Hi great to hear from you :) please share your mail id ! so that we can share the data sheet with you :)Do subscribe the channel for more updates : )

[@raviartgallery6466]

Good explanation

[@poojabhakuni464]

Can you please provide the code, it will be a great help!

[@edurekaIN]

Please share your email id with us (it will not be published). We will forward the code to your email address.

[@nahidchahin5716]

Nice video. I was really helpful. Please can you send me the source code??

[@vivanjain1746]

Great explanation. Can you share the code

[@edurekaIN]

Thank you. Please share your email id with us (it will not be published). We will forward the code to your email address.

[@kritinworld]

Well explained. Can you please share the source code?

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Good to know our contents and videos are helping you learn better . We are glad to have you with us ! Please share your mail id to send the data sheets to help you learn better :) Do subscribe the channel for more updates : ) Hit the bell icon to never miss an update from our channel : )

[@mahimsd7645]

Nice one ....good

[@habibasani8106]

Nice video. I was really helpful. Please can you send me the source code t practice

[@edurekaIN]

Hi Habiba! Can you please share your email id with us (it will not be published). We will forward you the source code to your email address.

[@Amitkumar-em4fm]

Nice Video and great explanation .Can i get the source code pls

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Thank you. Please mention your email id (it will not be published). We will forward the code to your email address.

[@arnavaakash8697]

can u please send the code to me...I found your very video helpful but I couldn't find code anywhere in the description as pointed in the video

[@edurekaIN]

Hey Arnav, glad you loved the video. If you could please mention your email id(we won't publish it) so that we can share the files with you.

[@WasimAkram-vq5if]

Great session

[@bpratima87]

can u please share the code it would be helpful Prior thank you

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Hey Pratima, hope you found the video informative. Please do share your email id(we won't publish it) so that we can mail the files to you. Cheers!

[@khanjanshah3823]

Sir, can you please provide this code?

[@rudrajadageethakrishna3171]

Sir please can you keep python live class pls sir

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[@mansigandhi7821]

I am not able to find the code i.e. jupyter notebook which sis mentioned in the course

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Please share your email id with us (it will not be published). We will forward the code to your email address.

[@vipulsharma8865]

All Right!

[@tanmaydhaundiyal8532]

The video is awesome, can i get the link to source code?

[@edurekaIN]

Hey Tanmay, we are glad you loved the video. Please do mention your email ID over here and we will send the files to you. Cheers!

[@digibro4496]

where is code in description

[@edurekaIN]

Hey Digi Bro, mention your email address and we will send it over. Cheers :)

[@sundayagu2078]

Excellent analysis. Thank you and remain blessed.