NOTE: This is an updated and revised version of the Decision Tree StatQuest that I made back in 2018. It is my hope that this new version does a better job answering some of the most frequently asked questions people asked about the old one. Support StatQuest by buying my book The StatQuest Illustrated Guide to Machine Learning or a Study Guide or Merch!!! statquest.org/statquest-store/
Hi Josh, great video! I have one question. When you are calculating the total Gini impurity based on the weighted average, why is it not (1 - weight)*Gini instead of (weight)*Gini? Since we want to minimize Gini, wouldn't the Gini value with the most sample size have its overall Gini reduced (as in (1 - weight)*Gini ) instead of increase (as in (weight)*Gini) ? Thanks!
@@haoyuanliu8034 The more data we have to support something, the more trust we have that that something is correct. Likewise, if I don't have much data to support something, then I should probably have less confidence that that something is correct. And that's what we're doing here. The more data observations we have in a leaf, the more data we have to support the predictions made by that leaf. Thus, the weight amplifies the gini value for the leaf for the most data.
Haven't watched them all yet but probably will. And even that you have and will receive more compliments, it's always worth keeping on thanking you for this amazing job!
I'd never seen a youtube comment section so full of thankful, enlightened and happy people. You must have revolutionized teaching. Thank you Josh, for these excellent videos. You rock!
Honestly Josh, you are a god-send for data science students. After getting an expensive Master's degree in Data Science, I still come back to your videos everytime I need a quick refresher or understand a tricky concept in detail. My professors, eventhough they are very knowledgable and good people, couldn't do half as much as you to teach these concepts given their rush to finish lectures within the hour and vacate lecture halls for he next class. Your videos are very comprehensive and well thought out. Thank you and keep going!
I never watched Andrew NG's OG course.... i just come back to these videos if I have any doubts or if I need to refresh my knowledge. Thanks a lot josh ;)
This channel helped me a loooot! It helps me from researching to looking for a job, from recreating myself to exploring the field of statistics and machine learning. You are the best! I can't express my gratefulness in words!
Hey Josh! I have not come across a better explanation of tree methods than on your channel. You've saved me countless hours of going through ISL e-book and still not understanding a thing. Thank you so much!! PS: The subtle humor is refreshing also.
I love this video ( in the same spirit of many other of your machine learning algorithm videos) because after watching it, I actually managed to code a simple classification tree on my own to just solidify the things I learned here, and after watching this video, all the parameters in scikit-learn DecisionTreeClassifier are making sense to me. Most of the ML videos and many of the classes out there only talk about very generalized, high-level ideas of these models. You don’t. You always do such a great job giving clear yet detailed explanation of the nitty gritty of these models. Between the ISLP/ISLR books and your videos I am able to gain basic understanding beyond just making api calls of caret in R or sklearn in python. It really made me feel like I am learning, instead of just typing formulas on the keyboard. Could never thank you enough ❤❤❤
Hi, would you mind sharing what textbook you are reffering to? I noticed there is a reference to some textbook in the video. I'm guessing it's referring to the Introduction to Statistical Learning with Applications in R, but I'm not sure about the edition, and at least in the electronic versions, I can't find the relevant information on page 321.
More important than teaching people statistics and machine learning, you teach people they are capable of understanding things they would of otherwise thought themselves incapable of understanding.
@@statquest Sir can you pls tell me how should i start ML as beginner. Is this the place that should start ua-cam.com/video/Gv9_4yMHFhI/v-deo.html from your tutorial
Your explanations are the best!! Instead of teaching the mathematical abstraction first, you teach with a small step by step example that removes the abstraction complexity, so then when reading the formal explanation I can understand it much better. That's the best teaching method, keep doing it this way :D
I don't know who are you but man you are the best instructor ever I have ever seen. I wish my math teacher met you, she was teaching us the same way you do 😍
This guy is amazing! I also love how he reminds us of what we were doing, why we were doing it and how we were doing it. Usually, halfway through my lectures I have forgotten where we came from and why we are doing what we're doing. Can't see the forest for all those trees... B)
Thank you, Josh. Based on the methods you provided I tried creating a Python function that calculates the GINI impurity for each independent variable, It really helped deepening my knowledge. thanks again.
I have been sitting on the edge of my seat rooting for the algorithm to figure out that age is the only valid indicator for whether people like an old movie. Only to realize that soda is a valid indicator to deduct somebodies age and that the final outcome suprisingly, makes sense.
about two weeks ago i was trying to learn how the slit is made on numerical data for best split. I was using python for this and was always setting the split space with np.linspace, to find the best split, but the way you showed with averaging a sorted list is very intuitive. If I have only watched this video it would let me save few days of learning how to manually calculate information gain and best split to better understand how DT is working. Great video!
Hey Josh, I am about to go into my last exam before I graduate and this is the last video I'm watching for a topic that was covered in a day I missed I'm sure you won't see this but thank you for all the help you've done
Hi Josh, Many many thanks for you invaluable videos which make complex concepts / models easier to understand! Not sure if you ended up finding where Gini comes from, Wikipedia has is as being named after and Italian mathematician. "Gini impurity Gini impurity, Gini's diversity index,[23] or Gini-Simpson Index in biodiversity research, is named after Italian mathematician Corrado Gini and used by the CART (classification and regression tree) algorithm for classification trees. " (source Wikipedia)
Thanks in a million! Very well explained. This is the nth time that I am watching this again. Great content. Awesome. I couldn't find this explanation--simply put anywhere else. “Great teachers are hard to find”. Grade: A++ 💥
@@statquest Yes he did , we don't really question what material professors use but , seeing the watermark , i came here to understand what the lesson was about and I wasn't disapointed
NOTE: This is an updated and revised version of the Decision Tree StatQuest that I made back in 2018. It is my hope that this new version does a better job answering some of the most frequently asked questions people asked about the old one.
Support StatQuest by buying my book The StatQuest Illustrated Guide to Machine Learning or a Study Guide or Merch!!! statquest.org/statquest-store/
Awesome work!
The very model of clarity. Thanks :)
Hi Josh, great video! I have one question.
When you are calculating the total Gini impurity based on the weighted average, why is it not (1 - weight)*Gini instead of (weight)*Gini?
Since we want to minimize Gini, wouldn't the Gini value with the most sample size have its overall Gini reduced (as in (1 - weight)*Gini ) instead of increase (as in (weight)*Gini) ?
Thanks!
@@haoyuanliu8034 The more data we have to support something, the more trust we have that that something is correct. Likewise, if I don't have much data to support something, then I should probably have less confidence that that something is correct. And that's what we're doing here. The more data observations we have in a leaf, the more data we have to support the predictions made by that leaf. Thus, the weight amplifies the gini value for the leaf for the most data.
Hello,
when it comes to variables like age: How do u decide if u should use "
The complexity of understanding the concepts and explaining them so simply show what a great teacher Josh is.
Thank you! :)
Josh, I just finished watching absolutely all your videos on this channel. Congratulations for them, you are the best!
WOW!!! That's a lot of videos! Thank you very much! :)
how much are you sponsoring? LOL
why did you do that, What do you do?
@@amaarmarco530 I am Data Scientist, and I wanted to have a really good knowledge about statistics
Haven't watched them all yet but probably will. And even that you have and will receive more compliments, it's always worth keeping on thanking you for this amazing job!
I'd never seen a youtube comment section so full of thankful, enlightened and happy people. You must have revolutionized teaching. Thank you Josh, for these excellent videos. You rock!
Thank you! :)
Honestly Josh, you are a god-send for data science students. After getting an expensive Master's degree in Data Science, I still come back to your videos everytime I need a quick refresher or understand a tricky concept in detail. My professors, eventhough they are very knowledgable and good people, couldn't do half as much as you to teach these concepts given their rush to finish lectures within the hour and vacate lecture halls for he next class. Your videos are very comprehensive and well thought out. Thank you and keep going!
Thank you very much! :)
I am half way through your Machine Learning playlist. It has been so helpful and resourceful, I can't put into words. Thank you Josh.
Thank you very much! :)
Save the environment by planting some decision trees
bam!
Environmentally friendly decisions
@@statquestDouble bam 🎉
Josh, you are just amazing ... you explained it so well. Whenever I get stuck, I return to your videos and clear it out ... thank you so much...
BAM! :)
You ability to simplify hard concepts into simple explanations is amazing, great video!
Thank you!
I never watched Andrew NG's OG course.... i just come back to these videos if I have any doubts or if I need to refresh my knowledge. Thanks a lot josh ;)
Bam! :)
If "love at first sight" is real, then this video made me love your way of teaching!
Hooray! Thank you very much! :)
This channel helped me a loooot! It helps me from researching to looking for a job, from recreating myself to exploring the field of statistics and machine learning. You are the best! I can't express my gratefulness in words!
Thank you very much! :)
This is one of best videos on Decision Trees on the internet. Thanks Josh!
Thank you!
Hey Josh! I have not come across a better explanation of tree methods than on your channel. You've saved me countless hours of going through ISL e-book and still not understanding a thing. Thank you so much!!
PS: The subtle humor is refreshing also.
Thank you very much! :)
I love this video ( in the same spirit of many other of your machine learning algorithm videos) because after watching it, I actually managed to code a simple classification tree on my own to just solidify the things I learned here, and after watching this video, all the parameters in scikit-learn DecisionTreeClassifier are making sense to me. Most of the ML videos and many of the classes out there only talk about very generalized, high-level ideas of these models. You don’t. You always do such a great job giving clear yet detailed explanation of the nitty gritty of these models. Between the ISLP/ISLR books and your videos I am able to gain basic understanding beyond just making api calls of caret in R or sklearn in python. It really made me feel like I am learning, instead of just typing formulas on the keyboard. Could never thank you enough ❤❤❤
Hooray!!! I'm so glad you enjoy my videos. :)
I will spent my first salary from the job by buying your merch and supporting your channel , you are just great prof
Hooray!!! Thank you very much! :)
hey bhai i need help from u to understand this concepts for my assignment, can u contact to me?
You are the REAL GOAT! The best and most intuitive textbook is ISL and your UA-cam video makes this even better. Hats off to your hard work.
Wow, thanks!
Hi, would you mind sharing what textbook you are reffering to? I noticed there is a reference to some textbook in the video. I'm guessing it's referring to the Introduction to Statistical Learning with Applications in R, but I'm not sure about the edition, and at least in the electronic versions, I can't find the relevant information on page 321.
Thank you Josh, there is no channel on UA-cam (or maybe on the Internet) that explains this topics as nifty as you do.
Thanks!
Oh great video. Wish the lecturers would have same knowledge about this topic as yours... Thanks man!
Glad it was helpful!
More important than teaching people statistics and machine learning, you teach people they are capable of understanding things they would of otherwise thought themselves incapable of understanding.
bam! :)
I'm not used to comment on youtube videos, but this one for sure deserves it. Thanks so much for the explanation, and keep up the good work!
Thanks, will do!
your method of teaching is so simple, yet so amazing
Thank you very much!
You are amazing. I really wish that University professors had the ability and drive to actually teach like this.
Thank you!
Gotta say it Everytime! Thank you for granting me clear vision of the concept!!
BAM! :)
amazing video, 18 minutes of your video conveys more useful information than a 3 hours lecture at my uni
Glad it helped!
I just became fan of yours....the way you teach complicated things with humour and fun, its simply amazing....
Thank you so much 😀
BAM!
You are the best teacher for Stats and ML!
Thank you!
By far the best explanation I’ve come across. Thank you so much!
Thanks!
best tutor alive on earth. thanks man. appreciate your hard work for us.
Wow, thanks!
Yet another fantastic stat-quest, Loved these for my class for Deep learning. Keep up the good work!
Thanks, will do!
The best teacher i ever had ....i will send a gift on teachers day Mr Josh!
Bam! :)
@@statquest Sir can you pls tell me how should i start ML as beginner. Is this the place that should start ua-cam.com/video/Gv9_4yMHFhI/v-deo.html from your tutorial
Thank god, i found your video. You explained it so well, that I literally couldn't control jumping in happiness.
Glad it helped!
The best teacher by far I've ever seen in my life! Thank you Josh!
Thanks!
who is here not just for statistics but for English pronunciation as well? Clearly explained and clearly pronounced!!!!
Thank you very much! :)
World's best video on Decision Tree Classifier 💚💚💚💚
Thank you!
Brilliant, thanks Josh - exactly the slow and steady explaination I needed
Thanks!
I am so happy I found this video. Thank you for making it. It is so clear how the decision tree actually works.
Glad it was helpful!
The explanation is so simple and rewarding too. Thank you.
bam!
Amazing video to learn Decision and Classification Trees from zero to hero!
bam!
Your explanations are the best!! Instead of teaching the mathematical abstraction first, you teach with a small step by step example that removes the abstraction complexity, so then when reading the formal explanation I can understand it much better. That's the best teaching method, keep doing it this way :D
Happy to help!
Hi Josh,your videos are the best in understanding the working of machine learning algorithms in the simplest way!!!
Thank you very much! :)
Absolutely Brilliant. Such a simple explanation. Love this vid
I'd like to thank you so much for making this stream cast available!
Thanks!
starting to regret why i need to go to school 3 days per wee, 5 hours per day for machine learning. listening to your videos beats every lecture.
bam!
with this channel, go to school clase is just waste time. Great teacher Josh is.
Thanks!
I don't know who are you but man you are the best instructor ever I have ever seen. I wish my math teacher met you, she was teaching us the same way you do 😍
Wow, thank you!
your 2 vids of Knn and this explain better than my 2 hrs lecture and 1 hr lab which done by my uni teacher.
thank you
Happy to help!
This guy is amazing! I also love how he reminds us of what we were doing, why we were doing it and how we were doing it. Usually, halfway through my lectures I have forgotten where we came from and why we are doing what we're doing.
Can't see the forest for all those trees... B)
Thank you so much! I'm glad you like my videos. :)
Thank you, Josh. Based on the methods you provided I tried creating a Python function that calculates the GINI impurity for each independent variable, It really helped deepening my knowledge. thanks again.
bam!
I have been sitting on the edge of my seat rooting for the algorithm to figure out that age is the only valid indicator for whether people like an old movie.
Only to realize that soda is a valid indicator to deduct somebodies age and that the final outcome suprisingly, makes sense.
bam! :)
You know your content is fire when even the professor at our university used your videos in his lectures.
bam!
about two weeks ago i was trying to learn how the slit is made on numerical data for best split. I was using python for this and was always setting the split space with np.linspace, to find the best split, but the way you showed with averaging a sorted list is very intuitive. If I have only watched this video it would let me save few days of learning how to manually calculate information gain and best split to better understand how DT is working. Great video!
Thank you!
Just found this channel, already know it's awesome, helps me a lot!
Bam! :)
this is BY FAR! one of the best explanations ever!
Thanks!
Thanks man! I just love how easy to follow your ’Quests are!
TRIPLE BAM!!! Thank you so much for supporting StatQuest!!! :)
You might be the best teacher I've ever had :D
Thank you very much! :)
Hey Josh, I am about to go into my last exam before I graduate and this is the last video I'm watching for a topic that was covered in a day I missed
I'm sure you won't see this but thank you for all the help you've done
Thanks and good luck on your exam! Let me know how it goes.
Josh, your videos do help me as visual Lerner a lot. Thanks.
Happy to help!
You are such an amazing teacher Josh!
Thank you! :)
All videos are golden. Thank you StatQuest!
Thank you!
Please I want u to know that u are something like jesus of statistic, the clarity of yours explanation has no competition at all, thank you
Thank you!
Just bought the book, hope it would help you to continue your work 🧑🎓
@@ettoremiglioranza2959 Hooray!!! Thank you so much for supporting StatQuest!!!
Best channel on youtube, such a treasure!
Wow, thank you!
Just fantastic! You are doing a job as great as ISLP!
Thanks a lot!
this was the most exciting and crystal clear explanation . thanks a lot
Thank you! :)
Thank you very much. Please continue creating videos like this. These helps a lot.
Thanks!
I would be working for NASA by now if all my teachers/Profs were as good and concise as Mr Josh!
bam!
tmwr is my ML exam and here i am brushing past my concept in x2 speed this man here is a legend i would suggest beginners to watch his videos
Thanks!
@@statquest keep teaching and entertaining us students love from India
@@devarghyaray Good luck with your exam! :)
Absolutely fucking brilliant. Love this video. Such a simple explanation. Brilliant.
Thanks!
Thank you SO much Josh. This has been the most helpful guide on decision trees I have come across. :)
Glad it was helpful!
Hi Josh,
Many many thanks for you invaluable videos which make complex concepts / models easier to understand!
Not sure if you ended up finding where Gini comes from, Wikipedia has is as being named after and Italian mathematician. "Gini impurity
Gini impurity, Gini's diversity index,[23] or Gini-Simpson Index in biodiversity research, is named after Italian mathematician Corrado Gini and used by the CART (classification and regression tree) algorithm for classification trees. " (source Wikipedia)
Thanks!
Very nicely explained! I can't find better explanation than this!! Double Bam!!
Glad you enjoyed it!
It's innovative way of teaching. thanks for creating and uploading.
Thank you!
Couldn't resist to thank you a SECOND TIME!!
Double bam!!! :)
Thanks for explaining many complex concepts in simplest way.....plz upload more data science basics
Thanks! I'll keep that in mind! :)
Even my mother could build a decision tree with this video.
bam!
Your explanations are always the best. Thank you
Thank you! :)
Thank you for explaining it in a so easy way to understand.
Thanks!
Josh...I love you man ...you really making the concepts clear n easy for us.. thanks, thanks n big thanks...Lots of Love from my side and INDIA...
Thank you very much! :)
Thanks in a million! Very well explained. This is the nth time that I am watching this again. Great content. Awesome. I couldn't find this explanation--simply put anywhere else. “Great teachers are hard to find”. Grade: A++ 💥
Thank you very much! :)
you talk to me like i'm 5 years old, and i LOVE it
bam!
Just what I needed to help me with my machine learning class
Bam! :)
You are amazing. Great content, pleasing visuals, and great songs.
Thank you very much! :)
CLEARLY EXPLAINED SIR THANK YOU!
Thanks!
How could anyone dislike "Cool As Ice?" Vanilla Ice is the man!
That is the eternal question! :)
wow...best explanation ever..I'm impressed. Thanks a lot
Glad you liked it!
Thank you for your explaination. It is so clear to understand.
Glad it was helpful!
Hey thank you so much. Your video is easy to follow. I can tell that you put efforts and heart in it!
Glad it was helpful!
Great explanation for the DT
!!!
Thank you!
Thank you a ton for these Josh, these explanations are super clear. Love the humor too.
Thank you very much! :)
Recently I have purchased your book. BTW Im from India. BAMM !!! Its nice
Thank you very much for supporting StatQuest!!! BAM! :)
That was very informative. I can do my homework thanks to this video. Thank you so much.
Glad it was helpful!
NOW YOU MADE IT MORE CLEAR COPARED TOT HE PREVIOUS VIDEO THANK YOU
THANK YOU!!! :)
This just happens to be using the same pdf file our professor provided , super helpful , thank you !!!
Hmmm...Are you saying your professor provided you with a PDF of this exact video?
@@statquest Yes he did , we don't really question what material professors use but , seeing the watermark , i came here to understand what the lesson was about and I wasn't disapointed
@@crowbartwisted8738 OK.
You're a hero Josh, thankyou 🧠
Thank you!
Why is there no one commenting about the subtle comedic genius this video has
bam! :)
such a simple and beautiful explanation...BAM!
Thank you!
what a great teacher>>>>
Thank you!
Josh, thanks for these videos and the awesome intros. Your channel really helps me study for my bioinformatics coursework and exams. Much love 💖
Good luck with your exams! :)
Thanks 🙏🏼💖
happy to say that knowledge people are 🥳still alive in the universe.....
:)
Best Explanation I have ever saw!!!
Thank you!