Hierarchical Clustering - Fun and Easy Machine Learning
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- Опубликовано: 18 сен 2024
- Hierarchical Clustering - Fun and Easy Machine Learning with Examples
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Hierarchical Clustering
Looking at the formal definition of Hierarchical clustering, as the name suggests is an algorithm that builds hierarchy of clusters. This algorithm starts with all the data points assigned to a cluster of their own. Then two nearest clusters are merged into the same cluster. In the end, this algorithm terminates when there is only a single cluster left.
The results of hierarchical clustering can be shown using Dendogram as we seen before which can be thought of as binary tree
Difference between K Means and Hierarchical clustering
Hierarchical clustering can’t handle big data well but K Means clustering can. This is because the time complexity of K Means is linear i.e. O(n) while that of hierarchical clustering is quadratic i.e. O(n2).
In K Means clustering, since we start with random choice of clusters, the results produced by running the algorithm multiple times might differ. While results are reproducible in Hierarchical clustering.
K Means is found to work well when the shape of the clusters is hyper spherical (like circle in 2D, sphere in 3D).
K Means clustering requires prior knowledge of K i.e. no. of clusters you want to divide your data into. However with HCA , you can stop at whatever number of clusters you find appropriate in hierarchical clustering by interpreting the Dendogram.
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This video could not have been any more clearer, it really helped me to understand the concepts. Make ANOTHER ONE :v
@Shepherd Johnathan I didn't ask for that.
Thanks so much!!! please ANOTHER ONE
These videos are outstanding - such concrete examples and clearly explaining pros and cons. You are a genius :-)
Haha 😁 I wish I was a genius but thank you so much. I'm really glad you enjoyed it!
Danko is thank you🙌🏾
Thank you very much. This is super helpful, will definitely return back to this video in the future.
yasss, thanks again! Im so ready for exam now.
💪😎
Your ML videos are the best ones I've come across for explaining concepts! I wish more people knew about them! In which video do you talk about distance metrics?
Hey Deepshika, thanks I really appreciate it 😁. Still don't have a video on that but will look into it
This is the best video on Hierarchical Clustering. Thank you.
Awesome, short but with all the important notes
Thank you Ron Lee :). I am really glad you enjoyed the video. If you have anything that you want me to make a video about, just use the hashtag #augmentedstartups with your comment and I'll see what I can do.
If you haven't already, check out my channel page to see all of the topics I've covered so far www.augmentedstartups.info/RUclips or check out our courses here www.augmentedstartups.com/store
I look forward to seeing you around! 👊
LOVE These Videos! so simple to understand and walking through the math really helps to understand why certain types of predictive algo's are used over others, your advantages disadvantages section is incredible, answers several questions i have been asking in working with data sets and helps to tweak the right predictions to the right type of algo. A+!!!! side note* completely unrelated to the educational value of your video's... barts teacher is Edna Krabapple* (not flanders) again, irrelevant to the value of the video's and thank you again for all the work that went into this, they have been immensely useful in my learning process to become a better data scientist :)
ANOTHER ONE
ANOTHER ONE
Awesome video series..this really helped to understand concepts
+Avadhut Talbar thank you so much and I'm really glad you enjoying this series :)
Great channel for educational videos, the best, very interesting !!
Great video, Thank you very much!
thank you for the informative videos! do you have one on k-means clustering? thankyou in advance!
The video really explains well and helps a lot!!!! thx!
I'm really glad it helped :)
very nicely explained.
Marge must be merged with cluster of her sisters first (they have same psrents => more common DNA ), and after Lisa must merge to that big cluster(Marge and tweens).
Very informative and entertaining, I'll definitely be watching more of your ML content 👍👍
Thank you nthabiseng moela :). I am really glad you enjoyed the video. If you have anything that you want me to make a video about, just use the hashtag #augmentedstartups with your comment and I'll see what I can do.
If you haven't already, check out my channel page to see all of the topics I've covered so far www.augmentedstartups.info/RUclips or check out our courses here www.augmentedstartups.com/store
or you can consider becoming a member of Augmented Startups and get access to Advanced Tutorials :)
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I look forward to seeing you around! 👊
Agglomerative clustering looks very similar to DBSCAN algorithm, at least visually.
Awesome! Can you explain what closeness function is and how it relates to clustering problem?
do you mean with Euclidean Distance? basically, each one of them points would have an X and Y value.
if you have 2 points (13,5) and (100, 10), then you get a new third point (20,15) using Euclidean Distance (or any other distance metric) you can see which of the original two points is closes to the new third point.
Simply I love it!
THNX
Need density based clustering !. Please do a video about it
Excellent video - thank you. At the end of each of the Fun & Easy ML videos you mention that the next video will deal with using the algorithm in Python. I can't see the Python videos on your channel though? Do they use SciKitLearn or programming from scratch?
+Harry Burn thank you Harry and glad you enjoyed it. :). Yes you cannot see it as ithe practical labs form part of my paid course on Udemy. Link is in description. There you will learn the practical side of machine learning.
thanks a lot!
You are most welcome :)
Love these vids
Such an awesome vid!
Thank you so much :)
thanks man u r awesome
thanks
thank you very much
+Mostafa Zaidoon you are most welcome, Mostafa 😋
Hi..can i use clustering if i need to make personalized ads for customers?
make a tutorial on Gaussian Mixture Model
Great video man!!!
Awesome way of learning Machine Learning :)
+Hrishikesh Kulkarni thank you so much for the comments. :) Glad you are enjoying them
thanks bruh
Can you please tell me the software for construct a dendogram
What program do you use to create this video?
Videoscribe sparkol
Cartoons don’t have ‘genetic codes’.
When dealing with the hierarchy of an animated series like the Simpsons, the family comes first and all other characters are secondary and celebrity guest voices would be the ‘third class’.
The only true measurement of any hierarchy, would be the number of episodes each character has directly appeared in.
Shouldn't all five girls have the same height in 2:33? Means, why are the twins and the daugther/mother clustered and separated from the single woman? In other words: Shouldn't there be three equivalent clusters in the first place? Instead of two?
Good question. It depends on what features you are looking at, it could be genetic similarity, height, gender and the list goes on. There are numerous ways in which you can cluster the input variables based on the features that you select
no st as fx or not ts a toolx
pathy selma and marge aren't sisters ?
Video was not HD.
Hop this vidéo in frensh :(