THANK YOU SOOOOO MUCH!!!!! After emailing my professor, and getting no real help, and spending days trying to figure it out on my own, you saved me! You were very clear, explained very well, and I now was able to complete my assignment. I can't thank you enough for this invaluable help! I wish professors and teachers were all this good!
I've been searching all over the internet for a simple explanation on how to do this and finally found yours. It was very clear and concise. Thanks for this!
The 3 hours before my exam I saw this video, fortunately single and complete linkage questions appeared on the last part of my machine learning's exam. Thank you very much to this video to get me have a better understanding :D
Thank you ! I am studying for my statistics exams. My Unis Documents on this matter are so bad. You really helped me understand it :) On to your next Video :)
great Videos Anuradha!!!!!!..... why you're not making any new videos for the last 4 years, your detailed explanation and attention to nuance is so amazing... I suggest you come back with more videos on ML & DL algorithms ...have a great day
thank u madam, it helped me a lot to understand, its easy, more clear explanation. In the video at 5:03 time, formula is shown wrong, i think a typing mistake. one question having yet is, aft forming a cluster [p3,p6], in the dist matrix, we replaced p3 place with [p3,p6]. why cann't we replace p6 place with [p3,p6]....... thank u adv.
when I calculated each distance in the calculator by the euclidean distance measuring formula, I have found lots of (0.01) differences in the calculation which can change the whole dendrogram, like in (p3,p2) you calculated 0.15 but it will 0.14.
Agreed -- the rounding errors in the distance matrix are problematic and should be corrected. Otherwise, those working through this example are likely to be confused when their own calculations yield different results. I would also suggest equalizing the axis scales for the x/y plot. The "stretch" in the x-axis relative to the y-axis is causing a visual disconnect between your calculated euclidean distances and the apparent closeness of points in the plot. For example, the (P2,P4) distance is 0.194 whereas the (P2,P5) distance is 0.143, but the axis scaling makes the (P2,P4) distance look like the shorter of the two.
Thank you for this hand calculation it does a good job of explaining what's going on. Would be useful to get a python code where you do the calculations from scratch using python
Ma'am, you have roughly drawn the dendogram. If we plot the dendogram by taking Thier respective values on X axis and Y axis, there will be completely different dendogram from what you hav drawn
![Hierarchical Agglomerative Clustering [HAC - Complete Link]](http://i.ytimg.com/vi/Cy3ci0Vqs3Y/mqdefault.jpg)
![Hierarchical Agglomerative Clustering [HAC - Average Link]](/img/n.gif)
THANK YOU SOOOOO MUCH!!!!! After emailing my professor, and getting no real help, and spending days trying to figure it out on my own, you saved me! You were very clear, explained very well, and I now was able to complete my assignment. I can't thank you enough for this invaluable help! I wish professors and teachers were all this good!
me too.. the video saved me for the last minutes before my exam, thank you so much
I've been searching all over the internet for a simple explanation on how to do this and finally found yours. It was very clear and concise. Thanks for this!
The knowledge you are sharing is so rare to find!! You save the world!!!
The 3 hours before my exam I saw this video, fortunately single and complete linkage questions appeared on the last part of my machine learning's exam. Thank you very much to this video to get me have a better understanding :D
Thank you on behalf of her
Exactly! This is what I was looking for. The Manual calculation and formation of the dendrogram. Thank you ma'am.
u must watch mahesh huddar video for better exlanation buddy
Thank you so much! You are a star! I have just started MSc after having graduated 20y ago. I am completely lost and you have been a great help.
Simple and to the point. The best explanation on youtube.
thankyou ma'am, the best thing about your channel is that you don't miss any step during calculations which makes it easy to understand 💯
The best explanation of agglomerative clustering example on the internet. Thank you so much!
I've been trying to figure this out for a couple days for class. Once you showed the MIN(dist) it all clicked. Thank you!
Thank you SOOOOOOOOO much！！ You explained the solution MUCH BETTER than my tutors did, this is so helpful!
Dr Bhatia, you are a gift to humankind!
Thank U so much. U helped me understand this Algorithm on the day before my Data mining final Exam =D
Thanks for this
Mam I have watched 3 videos of yours single link, complete link and average link and finally I'm able to understand Thank you mam for teaching us.
Wow. Clearly explained. Wonder if every lecture has the explanation ability like you
Thanks
this is old, but you just saved another cs student day!
Thanks so much❤❤ saved a lot of time before the exam
Lovely explanation, I have my masters exam tomorrow, just cleared all the doubts regarding agglomerative clusters, Thank you !!
Our professor is making us learn this in a softmore data structures class and implement into a project...I thought it felt out of scope for our level
Your explanatory skills are amazing ma'am. Please continue making more such learning videos.
thank you so much ma'am, this video really helped me a lot to understand the numerical of agglomerative hierarchical clustering
Best explanation on Agglomerative Clustering till now, thank you maam!!! I am clear as a crystal now.
I finaly understand HAC MIN. Thank you a lot!!!
very nice video and easy explanation.
Thank you so much, please keep uploading such videos.
Thank you so much for this! Need to know this for an exam in 2 days!
All the best
Thank you soooo much for your clear and detailed explanation!!!!♥ Never thought this concept could be so easy to understand!!~
Very Great and helpful and Very Very Easy Explanation. Understood Each bit. Thank You.
Thanks Ma'am...wonderful explanation and by this my exam syllabus got sorted...
Perfectly explained the concept.
Thank you ! I am studying for my statistics exams. My Unis Documents on this matter are so bad. You really helped me understand it :)
On to your next Video :)
Eye opening, thank you very much Anu! Much much respect to you!
This is exactly what I was looking for. Thank you so much.
thanks a lot ma'am, this is the best !!!!
Thank you Anuradha Bhatia, very good explanation i hope to see more of your explanations on various topics related to machine learning and data mining
Thank you for explaining how to solve this type of sums
:-D
Looking for more such videos..
Thank you so very much for the neat and detailed explanation. You have explained each and every step so very clearly..
Thank you very much.
Best one thank you so much tomorrow is my exam and now I’m confident in this sum🤩
you are a great teacher
I didn't get the thing that how are you calculating min of distance between cluster and a point
Splendid approach on your explanation. Thanks a lot!
Perfect explanation. Superb
your explanation is too good mam
Thank you so much it was really helpful for me to prepare final exam :)
You are a Life Saver. Thank You very much love.
Glad it helped!
Thank you mem, it is too useful to study the numerical taxonomy . Thanks a lot mem
Thank you for this excellent explanation.
Wonderful explanation and concept delivery, please make more videos like that,
Simply brilliant
Very easy and helpful. thanks
Really great presentation. I'd like to suggest a minor correction at 04:57 - formula for Euclidean distance ((x-a) + (y-b))^1/2
The Euclidean distance formula : x is written in place of y.
Perfect lecture
Very helpful tho ma'am
Thank you, your explanation is straight to the point
Awesome explanation! Hope to see more content from you in the future!
Hope to see You in VIT, as I am invited as a session trainer.
@@AnuradhaBhatia Oh cool that's amazing! We are excited to have you here!
Excellent teaching..
after lecturer teach me this subject, I definitely not understand what she teach, but after I hear once time then already understand
This teaching was better than my class teacher 😅
Thank you so much, It saved my time a lot
Thanks a lot. You save my life!
Finally I got this ... Thanks a lot
Thank you for your great explanation
Very nicely explained
thanks madam i dont know how to thank uu .you are doing lot of help means a lot.
thank you for explaining....
U explained it so easily mam❤️
great Videos Anuradha!!!!!!..... why you're not making any new videos for the last 4 years, your detailed explanation and attention to nuance is so amazing... I suggest you come back with more videos on ML & DL algorithms ...have a great day
Thanks a lot for this video. I finally understood how this algorithm is performed. Thanks a lot
It is really useful. Thanks a lot
Very clear and helpful.
Excellent explanation.Thanks a Ton
Brilliant !! Very helpful
Wonderful explanation. On point👏🏻👌
Thankyou maam for this video and explanation.... It really helped me❤️
Well explained .Thanks a lot.
thank u madam, it helped me a lot to understand, its easy, more clear explanation. In the video at 5:03 time, formula is shown wrong, i think a typing mistake. one question having yet is, aft forming a cluster [p3,p6], in the dist matrix, we replaced p3 place with [p3,p6]. why cann't we replace p6 place with [p3,p6]....... thank u adv.
This is still a little comfusing, but I got it so much better now. Thank you!
Awesome explanation thank you 😊
Very good explanation!
The quantitative value/level at which the 2 leafs or 2 clusters meet in the dendrogram should be made explicit.
when I calculated each distance in the calculator by the euclidean distance measuring formula, I have found lots of (0.01) differences in the calculation which can change the whole dendrogram, like in (p3,p2) you calculated 0.15 but it will 0.14.
Yes me too got the same (p3,p2) is 0.14 only..It will change the whole dendrogram
Agreed -- the rounding errors in the distance matrix are problematic and should be corrected. Otherwise, those working through this example are likely to be confused when their own calculations yield different results.
I would also suggest equalizing the axis scales for the x/y plot. The "stretch" in the x-axis relative to the y-axis is causing a visual disconnect between your calculated euclidean distances and the apparent closeness of points in the plot. For example, the (P2,P4) distance is 0.194 whereas the (P2,P5) distance is 0.143, but the axis scaling makes the (P2,P4) distance look like the shorter of the two.
Bro it's not the fault of sums ,may be it's u ,ur dumb in basic maths so do the 6 7 grade again
Many thanks mam. Nice tutorials
Thank you for this hand calculation it does a good job of explaining what's going on.
Would be useful to get a python code where you do the calculations from scratch using python
Thanks for this video! It was very clearly explained..
Well explained.
Amazing explanation, i thank you so so so much!
nice one Anuradha ....
Thank you madam, this cleared a big doubt I had.
thank you ,perfect explain
Very nice explanation Keep up the good work Glod Bless you !!
Thank you, great video
3:20 - Single Link
Thank you sooo much. It's a very clear explanation of this content!
excellent example , the best in UA-cam :)
Ma'am, you have roughly drawn the dendogram. If we plot the dendogram by taking Thier respective values on X axis and Y axis, there will be completely different dendogram from what you hav drawn
Thank you very much. Such an great explaination.
What if we got two minimum values as same in distance matrix and then which one to consider first? Time at 5.45
very good explanation.
Saved my day😀
Thanks, Ma'am. I like your teaching methodology.
Thank You so Much ma'am...
thank you my lady
Great tutorial, You are awesome
Thank you for the presentation. Have a better understanding of dendograms now.
you're the best :)