StatQuest: Hierarchical Clustering

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  • เผยแพร่เมื่อ 30 ม.ค. 2025

ความคิดเห็น • 379

  • @statquest
    @statquest  2 ปีที่แล้ว +12

    Support StatQuest by buying my books The StatQuest Illustrated Guide to Machine Learning, The StatQuest Illustrated Guide to Neural Networks and AI, or a Study Guide or Merch!!! statquest.org/statquest-store/

  • @Aemilindore
    @Aemilindore 3 ปีที่แล้ว +163

    You're a person who saved me lots of time and pain. Thank you. I wish you the best

    • @statquest
      @statquest  3 ปีที่แล้ว +4

      Thank you very much! :)

  • @kristinomalley4519
    @kristinomalley4519 ปีที่แล้ว +27

    You are, and I cannot stress this enough, a national treasure!! The ease in how you explain things that have eluded me for over a decade and make it click is truly a gift. Thank you so freaking much!!!

    • @statquest
      @statquest  ปีที่แล้ว +2

      Wow, thank you!

  • @anamulmbdu
    @anamulmbdu 6 ปีที่แล้ว +206

    The intro song removed my fear of clustering. Thanks for the awesome video.

    • @nemothekitten3994
      @nemothekitten3994 2 ปีที่แล้ว +3

      going on a statequest😌

    • @w花b
      @w花b 3 หลายเดือนก่อน

      ​@@nemothekitten3994 aww...

  • @julieboissiere4553
    @julieboissiere4553 2 ปีที่แล้ว +17

    I used to watch your videos while I was a student. It’s been 3 years since my graduation and I’m still here (I’m changing jobs and need to review some stuff).
    Thank you a lot for your incredible work

    • @statquest
      @statquest  2 ปีที่แล้ว +8

      Congratulations on the new job! BAM! :)

  • @fadikhattar290
    @fadikhattar290 2 ปีที่แล้ว +6

    I still don't believe how this content is free. Thank you sir!

  • @yamikag8363
    @yamikag8363 2 ปีที่แล้ว +4

    your videos help me see the "big picture" of concepts. after your videos, I can actually understand what is going on and why we are doing something. Thank you!

    • @statquest
      @statquest  2 ปีที่แล้ว

      Happy to help!

  • @chikken007
    @chikken007 4 ปีที่แล้ว +4

    I already watched some of your videos. This one I watched because I want to apply hierarchical clustering in my thesis. It is about time I buy one of your sweaters. I hope this supports you. Thanks for all the truly great explanations.THANK YOU!

    • @statquest
      @statquest  4 ปีที่แล้ว +1

      Thank you very much!!! :)

  • @stephenwood9252
    @stephenwood9252 2 ปีที่แล้ว +5

    Love your videos. The fact that you make it so simple shows the depth of your understanding.

  • @rajshrestha9484
    @rajshrestha9484 5 ปีที่แล้ว +56

    I can't thank you enough. Such clear and helpful explanations. Great.

  • @KL1_Khaled
    @KL1_Khaled 5 หลายเดือนก่อน +3

    Even after 7 years, you still the saver

    • @statquest
      @statquest  5 หลายเดือนก่อน +2

      Glad I could help!

  • @scraps7624
    @scraps7624 2 ปีที่แล้ว +7

    This channel is a treasure! Absolutely incredible job my man

    • @statquest
      @statquest  2 ปีที่แล้ว +1

      Thank you so much 😀!

  • @pragyamishra9083
    @pragyamishra9083 3 ปีที่แล้ว +5

    The visualizations and simplicity of explanations as well as great examples motivate me to keep learning. Thank you so much for making it so interesting. I'll try to do my bit by buying a t-shirt. 😊

  • @davidescobar4449
    @davidescobar4449 5 ปีที่แล้ว +3

    I have to congratulate you for this video, it gives the basic notions of the hierarchical cluster easy and fast. Bravo!

  • @jingsilu5568
    @jingsilu5568 2 ปีที่แล้ว +1

    Thank you for clearly explaining the details at a moderate speed! You save me lots of time!

  • @websciencenl7994
    @websciencenl7994 2 ปีที่แล้ว +1

    StatQuest is the Best! Teaching is an art...and these are master pieces.

    • @statquest
      @statquest  2 ปีที่แล้ว

      WOW! Thank you very much! :)

  • @liranzaidman1610
    @liranzaidman1610 4 ปีที่แล้ว +19

    Very nice.
    I use this in Python and it's a really good way to cluster.
    Another thing - from coding aspect, it's only 1 line of code in Seaborn, very easy.

    • @statquest
      @statquest  4 ปีที่แล้ว +1

      Thanks for sharing!

  • @KasperRasmussen-z3y
    @KasperRasmussen-z3y ปีที่แล้ว

    This channels is truly a treasure trove! I was wondering if you could do a video on consensus clustering? I.e. how to evaluate clustering across multiple models and parameters. You are awesome!

    • @statquest
      @statquest  ปีที่แล้ว

      I'll keep that in mind.

  • @nnnyin6967
    @nnnyin6967 ปีที่แล้ว +1

    I am preparing my actuarial exam and you saved me a lot❤

    • @statquest
      @statquest  ปีที่แล้ว +1

      Good luck! :)

  • @patolizac23
    @patolizac23 หลายเดือนก่อน +1

    my teacher keeps flying to new york and doesn't teach us crap about this so thank you for this pookie

    • @statquest
      @statquest  หลายเดือนก่อน

      Thanks!

  • @loftyTHEOWNER
    @loftyTHEOWNER 3 ปีที่แล้ว +2

    I would like to add that:
    - single-linkage (comparing the closest points of 2 clusters) tends to form more elliptic clusters;
    - complete-linkage tends to form more globular clusters.
    So, that means that not scaling your data, scaling with a StandardScaler, or with a MinMaxScaler will affect your clustering.

  • @HiasHiasHias
    @HiasHiasHias 7 หลายเดือนก่อน +2

    StatQuest never disappoints

    • @statquest
      @statquest  7 หลายเดือนก่อน

      BAM! :)

  • @brunomartel4639
    @brunomartel4639 4 ปีที่แล้ว +127

    this video proved that "hard" stuff =badly explained stuff

    • @sindhujas7807
      @sindhujas7807 4 ปีที่แล้ว +1

      so fuckin true. Not sorry for swearing. Happy learning guys

    • @gummybear8883
      @gummybear8883 3 ปีที่แล้ว +4

      if you can't explain something in simple terms, then you don't understand it that well.

    • @julius4858
      @julius4858 3 ปีที่แล้ว +7

      @@gummybear8883 or you've been a professor for 20 years and are so deep into a topic that you completely forgot how people approach new problems. Your sentence really only applies to novices trying to be teachers.

    • @MungoBootyGoon
      @MungoBootyGoon 3 ปีที่แล้ว +6

      @@julius4858 We could just change it to: if you can't explain something in simple terms, then you can't teach it that well.

    • @julius4858
      @julius4858 3 ปีที่แล้ว

      @@MungoBootyGoon Yeah, that is absolutely true. Many of my professors for theoretical computer science are experts on various fields but man do their explanations suck. That's why I have to watch youtube videos for stuff like this.

  • @farzanaferdousi9885
    @farzanaferdousi9885 3 ปีที่แล้ว +1

    Your explanation is very clear to me and i see all your video, you are very friendly to me. I like you very much.

    • @statquest
      @statquest  3 ปีที่แล้ว +1

      Thank you! 😃

  • @abhayjoshi2121
    @abhayjoshi2121 2 ปีที่แล้ว +1

    You are simply amazing !! I love your style and simplicity and the word is BAM! .. your videos are very informative and worth going through... thanks for all your hard work in simplifying the complex topics

    • @statquest
      @statquest  2 ปีที่แล้ว

      Thank you so much!!

  • @jonathanl7204
    @jonathanl7204 ปีที่แล้ว +2

    Thank you. Better than university teaching

  • @calebsawe8307
    @calebsawe8307 3 ปีที่แล้ว +1

    I am super grateful for this video. You are such an excellent teacher! Thank you for being such a "you"

    • @statquest
      @statquest  3 ปีที่แล้ว

      Wow, thank you!

  • @vishk123
    @vishk123 ปีที่แล้ว +1

    Thank you for allowing me to ascend the stats hierarchy!

  • @gurkanyesilyurt4461
    @gurkanyesilyurt4461 4 ปีที่แล้ว +1

    you saved yet another day Josh. Thank you

  • @Paulamiz
    @Paulamiz 3 ปีที่แล้ว +2

    Watching this after watching your more recent videos. Missed your 'BAM's a lot!!! You should remake these old videos again! Thanks :)

    • @statquest
      @statquest  3 ปีที่แล้ว +2

      bam! :)

    • @Paulamiz
      @Paulamiz 3 ปีที่แล้ว +2

      @@statquest 😍

    • @vakarthi4
      @vakarthi4 3 ปีที่แล้ว

      Found this gem of a channel today. Agreed on the fun rhymes and puns.

  • @2327853
    @2327853 5 ปีที่แล้ว +2

    @StatQuest please explain probability and Naive Bayes. Thanks in advance! I am a huge fan of your way of teaching and your small songs creations. Keep up the good work!

    • @statquest
      @statquest  5 ปีที่แล้ว

      Thanks! Naive Bayes is on the to-do list.

    • @createyouridea8602
      @createyouridea8602 5 ปีที่แล้ว

      @@statquest waiting. plz .

  • @congchen170
    @congchen170 7 ปีที่แล้ว

    Joshua's video is always helpful. Next time, probably k-means clustering.

  • @marahakermi-nt7lc
    @marahakermi-nt7lc ปีที่แล้ว +2

    ohh my god thanks josh u are so brilliant i think marvel should add another new superhero "josh starmer the life saver"

  • @옹늬야아
    @옹늬야아 ปีที่แล้ว +1

    You saved my life😇 Thank you very much.
    And I think the link for the sample code in R isn't available right now...

    • @statquest
      @statquest  ปีที่แล้ว

      Yep, that's a really old link. Here's a new one: statquest.org/statquest-hierarchical-clustering/

  • @anastasiyakuznetsova8797
    @anastasiyakuznetsova8797 3 ปีที่แล้ว +1

    The best as always! Love this channel! It's super easy to understand

  • @isha996
    @isha996 6 ปีที่แล้ว +1

    Please add a video on Latin Square design, Joshua!
    I am going to pass my stats final tomorrow, only because of your videos :D
    your students are lucky.

    • @isha996
      @isha996 6 ปีที่แล้ว +1

      The CPA and clustering question was worth 30% of total marks on my exam today, and I managed to write them so well only because of your videos. you're a savior. Thank you!!

  • @99harshini
    @99harshini 5 ปีที่แล้ว +6

    Absolutely brilliant..Thank you sooo much for your time and effort!

  • @zzzluke8906
    @zzzluke8906 ปีที่แล้ว +1

    Hi Josh, amazing video as always. Think you can come up with video on how to determine the best number of clusters to have? I get the Elbow method, but I really struggle with the inconsistent method. I was looking at the inconsistency coefficients, and I am confused to do they include singleton clusters, or are singleton clusters excluded. I am also confused about what exactly is the "jump" in the inconsistent coefficient that we are supposed to look out for.

    • @statquest
      @statquest  ปีที่แล้ว

      I'll keep that topic in mind.

  • @proggenius2024
    @proggenius2024 9 หลายเดือนก่อน +1

    awesome content and delivery

    • @statquest
      @statquest  9 หลายเดือนก่อน

      Glad you think so!

  • @MihirSriramVadali
    @MihirSriramVadali 7 หลายเดือนก่อน

    Great channel. Clearly explained all most all the topics i watched on ML. Here one question what does gene stands for is it features of the data ?

    • @statquest
      @statquest  7 หลายเดือนก่อน

      Yes, it's a feature.

  • @saipanchajanya5980
    @saipanchajanya5980 5 ปีที่แล้ว +1

    This is Awesome......
    Please Make a session on K Modes, KNN and K Prototypes

    • @statquest
      @statquest  5 ปีที่แล้ว

      Here's a complete list of my videos so far: statquest.org/video-index/

  • @manuelsokolov
    @manuelsokolov ปีที่แล้ว +1

    Dear StatQuest! Thank you for the explanation.
    1. What is the best would you would evaluate the algorithm (silluete score,...) to decide which clustering method and distance to use ( i undestand that silluete score is good to choose the number of k but not to decide between algorithms)?
    To decide the best algorithm i have been ploting PCA and color label by clusters created this way understanding if the clusters make sense or not? (however it is known by literature that PCA does not work well to evaluate binary data)
    2. In the case that the data is binary, (e.g instead of expression data, genomic alteration data) what kind of distance would you use?
    Best Regards, Manuel

    • @statquest
      @statquest  ปีที่แล้ว

      1) I guess it depends. If I had "training" data, with known categories, I would compare how many times the data were correctly and incorrectly grouped. Otherwise, it really just boils down to subjective preference.
      2) If you measure a lot of things, the euclidian distance will still work in this situation.

  • @mountainsunset816
    @mountainsunset816 2 ปีที่แล้ว +2

    The opening is always funny

  • @muhammadiqbalmarzuki
    @muhammadiqbalmarzuki 4 ปีที่แล้ว +1

    This video is super duper bam bam double double bam!
    Will you cover more advanced clustering techniques such as model-based clustering (MCLUST) and weighted gene co-expression network analysis (WGCNA)? I'm learning about these things now for my research, and will be very grateful if you can cover these topics for me. Thanks! :)

  • @preranadas4037
    @preranadas4037 5 ปีที่แล้ว +4

    Hello Josh! The videos are soooooooo goooood! These are BAMMMMM Good!!
    1 request - Could you please create a video on LCA - Latent Class Analysis? Maybe by comparing it to k-means clustering? I cannot be more thankful!

    • @LoriSchomp
      @LoriSchomp 4 ปีที่แล้ว

      would like this too

  • @eamiller12
    @eamiller12 3 ปีที่แล้ว +1

    THANK YOU! This is has been SO HELPFUL!

  • @davidcartwright337
    @davidcartwright337 5 ปีที่แล้ว +2

    great videos, I like the way you explain these topics

  • @fabiomaia3433
    @fabiomaia3433 4 ปีที่แล้ว +3

    Hey Josh! Your videos are great! Thank you for the effort you've put on it!
    If you allow me... have you considered making videos explaining DBSCAN and HDBSCAN?

    • @statquest
      @statquest  4 ปีที่แล้ว +2

      Yes, I've thought about those topics and may make a video about them.

  • @moikanal4625
    @moikanal4625 หลายเดือนก่อน +1

    thanks for amazing lessons

    • @statquest
      @statquest  หลายเดือนก่อน

      Double Thanks!

  • @emamulmursalin9181
    @emamulmursalin9181 4 ปีที่แล้ว +2

    Great explanation Josh! Just one question, are we clustering samples(data points) or the Genes(features)? If we are clustering Genese, does not it mean that we are just clustering the correlated features?

    • @statquest
      @statquest  4 ปีที่แล้ว

      In this video we are clustering the genes, and yes, the idea is that correlated features are brought together. We could even just calculate the correlation coefficient for each pair and cluster based on those values.

    • @emamulmursalin9181
      @emamulmursalin9181 4 ปีที่แล้ว

      @@statquest Thanks for your reply.
      But I have seen some other blogs where authors are plotting 2D data points and using hierarchical clustering. So in real life we use hierarchical clustering for data clustering or feature clustering?

    • @statquest
      @statquest  4 ปีที่แล้ว

      @@emamulmursalin9181 I'm not sure what you mean by "data" clustering, however, we can cluster the rows or the columns with similar ease. It doesn't matter if one is features and the other is samples.

    • @emamulmursalin9181
      @emamulmursalin9181 4 ปีที่แล้ว

      @@statquest Sorry for using an unclear term. Actually I meant "samples" by using the term "data".
      So, can hierarchical clustering be used for "feature clustering" (for example, finding correlated features and remove the redundant features) and also as "sample clustering" (e.g. just like K means clustering ) ?

    • @statquest
      @statquest  4 ปีที่แล้ว +1

      @@emamulmursalin9181 Yes. We can cluster the rows just as easily as we cluster the columns.

  • @shamanthrajreddy1230
    @shamanthrajreddy1230 2 ปีที่แล้ว +1

    Excellent explanation!

  • @rodrigohaasbueno8290
    @rodrigohaasbueno8290 6 ปีที่แล้ว +1

    I love this channel so much

    • @statquest
      @statquest  6 ปีที่แล้ว

      Thank you! :)

  • @tudorpricop5434
    @tudorpricop5434 ปีที่แล้ว

    At 7:28, we calculated the number 3.2 being the difference between gene 1 and gene 2. But the whole purpose of calculating is to figure out which gene is the most similar with gene 1 (for example).
    Now my question: After we compute the values between [gene 1 and gene 2], [gene 1 and gene 3] and [gene 1 and gene 4], we select the gene with the SMALLEST VALUE as the most similar gene to gene 1 ? Or the BIGGEST VALUE ? I think the smallest, but just to be sure..

    • @statquest
      @statquest  ปีที่แล้ว

      In this case we want the smallest distance, which means the most similar.

  • @cfonsecaparis812
    @cfonsecaparis812 3 ปีที่แล้ว +1

    Hi Josh, I am really enjoying your videos specially the wha whas and bam !! , you make stats sound easy but also fun! Thank you! I wonder if you could please do a video to explain the different uses of PCA and HCA, when do you use one or the other? In the mean time I will watch your videos on PCA and HCA :) hooray!

    • @statquest
      @statquest  3 ปีที่แล้ว

      BAM! Thank you very much! I'll keep that topic in mind.

  • @robertogff
    @robertogff 4 ปีที่แล้ว

    Congratulations! your video is so great! you explain is a very clear and simple way.

    • @statquest
      @statquest  4 ปีที่แล้ว

      Thank you! 😃

  • @kurniadi-5492
    @kurniadi-5492 3 ปีที่แล้ว +2

    it doesn't define if it's must be from the shortest Euclidean or what and basically what makes the dendogram become shorter from another

    • @statquest
      @statquest  3 ปีที่แล้ว

      I'm not sure I understand your comment. Can you clarify?

  • @mayconmarcao4554
    @mayconmarcao4554 2 ปีที่แล้ว +1

    Hey Josh, what is the difference between PCA and Hierarchical Clustering? Could you give me an example for each one? I know some people say " PCA groups variables " and "HC groups obsvervations". I think the output from each one represent that exaplanation. But it seems we could use both techniques to answer the same question...

    • @statquest
      @statquest  2 ปีที่แล้ว +1

      Although both methods can be applied to the exact same problem (and frequently are both applied to the same problem), they have different strengths. PCA, for example, has loading scores, which would tell us how much each individual variable contributes to the clustering. In contrast, hierarchical clustering gives us a nice heatmap style graph that makes it easy to see the big picture in how and why things are similar and different. I say "try them both."

    • @mayconmarcao4554
      @mayconmarcao4554 2 ปีที่แล้ว +1

      @@statquest BAMM! I got it. Thank you Sir!

  • @CapoeiraPiper
    @CapoeiraPiper 4 ปีที่แล้ว +1

    Man your videos are soo super helpful! THANK YOU (ps consider the color library viridis to make it easier for the colorblind)

  • @LetWorkTogether
    @LetWorkTogether 5 ปีที่แล้ว +3

    I love this. Your video is wonderful!

    • @statquest
      @statquest  5 ปีที่แล้ว

      Thank you! :)

  • @ankitabhavsar886
    @ankitabhavsar886 7 หลายเดือนก่อน +1

    the intro.......nice one bro🖐

    • @statquest
      @statquest  7 หลายเดือนก่อน

      bam! :)

  • @hamidkiangaikani
    @hamidkiangaikani 3 ปีที่แล้ว +1

    4.4 K likes, zero dislikes! You're awesome. Thanks very much

  • @jovanmampusti4025
    @jovanmampusti4025 3 ปีที่แล้ว +1

    Thank you so much sir! This is very helpful and very informative.

    • @statquest
      @statquest  3 ปีที่แล้ว +1

      Glad it was helpful!

  • @python_information601
    @python_information601 3 ปีที่แล้ว +1

    Nice explanation 👍👍

  • @mikecy5507
    @mikecy5507 2 ปีที่แล้ว

    Great channel! Clear explanations. In HCA, could you not follow up the clustering of rows (genes) by clustering the columns (samples)? Is this automatically done? Does not seem like the best heatmap would be produced if you just cluster/shuffle rows. Would have to cluster/shuffle columns, too, right? Also, must/should the data be standardized first?

    • @statquest
      @statquest  2 ปีที่แล้ว

      You can cluster both columns and rows. And sometimes standardizing helps, sometimes it doesn't. It's worth trying both options.

    • @mikecy5507
      @mikecy5507 2 ปีที่แล้ว +1

      @@statquest Thanks!

  • @lazyboy7521
    @lazyboy7521 3 ปีที่แล้ว

    Great video! There is a minor mistake around 8:21. You should replace "sample" by "gene" in calculating the distance, i.e., |difference in gene #1| + |difference in gene #2| +...

    • @statquest
      @statquest  3 ปีที่แล้ว

      I believe the video is correct. For details, see: 6:01

  • @alyssawang144
    @alyssawang144 3 ปีที่แล้ว +1

    fantastic explanation, thank you so much for this video.

  • @oliviagallupova9199
    @oliviagallupova9199 5 ปีที่แล้ว +1

    You saved me a week

  • @datdao6982
    @datdao6982 4 ปีที่แล้ว

    Hi just a question. At 7:16, if I'm not mistaken, then gene 1 and 2 are analogous to variable 1 and 2( aka x & y in 2-dimension dataset). So shouldn't the distance be sqrt( (x1-x2)^2 + (y1-y2)^2 ) or sqrt( (1.6-0.5)^2 + (-0.5+1.9)^2 ) ? Sorry if it may seem a stupid question, but since I'm not that good at maths in general I need to turn everything into the basics to understand. Thank you

    • @statquest
      @statquest  4 ปีที่แล้ว +1

      In this example we are trying to find how how similar (or different) Gene 1 is to (or from) Gene 2 across all samples, so we are comparing the distances between Gene 1 and Gene 2 in both samples. In other words, if both genes have similar values in Sample #1 and similar values in Sample #2, then we will consider both genes to be similar. In contrast, if the values for Gene 1 and 2 are different from each other in Sample #1 and different from each other in Sample #2, then we will consider the genes to be very different from each other. Thus, we are looking at the difference in gene within each sample.
      In contrast, you are asking to look at the sample differences within each gene. This would tell us that Sample #1 and Sample #2 are similar or not, and, in this example, we are not interested in that. Does that make sense?

    • @datdao6982
      @datdao6982 4 ปีที่แล้ว +1

      @@statquest I kinda get it. Thank you.

  • @setareht7546
    @setareht7546 3 ปีที่แล้ว

    Thank you for all your videos clearly explaining complex concepts. Can you also make video(s) on different bi-clustering methods?

    • @statquest
      @statquest  3 ปีที่แล้ว

      I'll keep that in mind.

  • @ramsha8540
    @ramsha8540 9 หลายเดือนก่อน

    10:08 do you have any videos that talk about clustering in R?
    Thankyou for all your explanations btw!!

    • @statquest
      @statquest  9 หลายเดือนก่อน

      Unfortunately, no. :(

  • @saikiranjajula2033
    @saikiranjajula2033 4 ปีที่แล้ว +1

    Thank You Sir, It was awesome to learn from you.

  • @patriciacontreras8435
    @patriciacontreras8435 9 หลายเดือนก่อน

    Thank you very much!🥰 You saved my life 🥲
    I have a question, if my dataset has continuous variables (ex. income) and a discrete variable (ex. number of children in the household). How can I measure the distance between them? Thank you!!!

    • @statquest
      @statquest  9 หลายเดือนก่อน +1

      You can use one-hot-encoding th-cam.com/video/589nCGeWG1w/w-d-xo.html or you can use a random forest to do the clustering th-cam.com/video/sQ870aTKqiM/w-d-xo.html

    • @patriciacontreras8435
      @patriciacontreras8435 9 หลายเดือนก่อน +1

      @@statquest Thanks again! I think I will learn a lot if I subscribe to this channel 🥰🥰

  • @HanyMostafa-sk9ml
    @HanyMostafa-sk9ml หลายเดือนก่อน

    The part that I don’t understand is the top blue and orange, did you apply hierarchical classification on the genes and on the samples ?

    • @statquest
      @statquest  หลายเดือนก่อน

      What time point in the video, minutes and seconds, are you asking about?

  • @fellsantfernandoargentin2072
    @fellsantfernandoargentin2072 6 ปีที่แล้ว

    Congratulations from Brazil!

  • @tymothylim6550
    @tymothylim6550 3 ปีที่แล้ว +1

    Thank you very much for this video! It was really well done :)

    • @statquest
      @statquest  3 ปีที่แล้ว

      Glad you liked it!

  • @govamurali2309
    @govamurali2309 3 ปีที่แล้ว

    Josh, how do we figure out the colors in the first place? @8:47..Say we measure the genes. Red denotes value from 0.8-1, blue denotes values from 0.1-0.2. Am I right?

    • @statquest
      @statquest  3 ปีที่แล้ว +1

      The coloring is actually arbitrary. Usually we like to have a gradient from the maximum value to the minimum value, but there is no rule that says we should only use 2 colors. We could use 3 or more. The idea is simply to create an image that is informative and useful.

    • @govamurali2309
      @govamurali2309 3 ปีที่แล้ว

      @@statquest Thanks Josh!!

  • @balajicanchi5538
    @balajicanchi5538 7 ปีที่แล้ว

    Explained in a simple manner.

  • @LBsCuriosity
    @LBsCuriosity 5 ปีที่แล้ว

    really awesome video! This will help me with my test. Thank you!

  • @urjaswitayadav3188
    @urjaswitayadav3188 7 ปีที่แล้ว

    Great explanation. Thanks StatQuest!

  • @MrKingoverall
    @MrKingoverall 5 ปีที่แล้ว +2

    I LOVE YOU JOSH !

  • @surbhardwaj1721
    @surbhardwaj1721 3 ปีที่แล้ว

    Amazing explanation. Please make a video on Cluster evaluation. :)

    • @statquest
      @statquest  3 ปีที่แล้ว

      I'll keep that in mind.

  • @sickleharvestsleeks
    @sickleharvestsleeks 3 ปีที่แล้ว

    9:44 average clusters is mean linkage; centroid is centroid of a cluster?

    • @statquest
      @statquest  3 ปีที่แล้ว

      I'm not sure I understand your question.

  • @aggelosdidachos3073
    @aggelosdidachos3073 4 ปีที่แล้ว

    Hello, I am Angelos Didachos and I have a question for StatQuest. 9:54 Is the way of comparing the point to the cluster same as before? That is, Manhattan distance, Euklidian distance etc ?

  • @anthonychan4478
    @anthonychan4478 6 ปีที่แล้ว +3

    Hi Joshua, can you do a video on Gaussian Mixture Models? Also, your videos are awesome! Keep it up.

    • @statquest
      @statquest  6 ปีที่แล้ว +6

      The good news is that is already on the To-Do list. I'll bump it up a notch since you requested it as well.

    • @jordanmakesmaps
      @jordanmakesmaps 6 ปีที่แล้ว +2

      @@statquest, make that two requests! Thanks!

    • @statquest
      @statquest  6 ปีที่แล้ว

      @@jordanmakesmaps Cool! It's in the top 10 things for me to do, so hopefully I'll get to it soon.

    • @jacobmoore8734
      @jacobmoore8734 5 ปีที่แล้ว +1

      @@statquestYes! Anytime people start talking about gaussian mixture models, EM, "sampling the posterior", and MCMCs - I get cold sweats.

  • @mojtabasardarmehni453
    @mojtabasardarmehni453 4 ปีที่แล้ว +1

    Great as always! Thanks.

    • @statquest
      @statquest  4 ปีที่แล้ว

      Thank you! :)

  • @sonakshigarg4273
    @sonakshigarg4273 5 ปีที่แล้ว

    You can explain the same concept with may be some other datasets and better visualisation other than heatmap

  • @the_data_panda
    @the_data_panda 6 ปีที่แล้ว +2

    @StatQuest with Josh Starmer, in this video you are clustering and combining genes (the attributes of data), aren't you supposed to cluster and combine the samples? that's the inverse of the approach shown

    • @statquest
      @statquest  6 ปีที่แล้ว +5

      You can cluster the samples or the genes, or both! It all depends on the question you are asking. For example, if I have some healthy people and some sick people, I might be interested in clustering the people (to see if healthy people form one cluster and unhealthy people form another) or I might be interested in clustering the genes. In this case I would find out which genes are correlated and up-regulated in healthy people compared to unhealthy people. Or I could do both. Does that make sense?

  • @yyma8037
    @yyma8037 4 ปีที่แล้ว

    Great video!
    Do you have any plans to talk about co-clustering, look forward to it.

  • @maikfranke2303
    @maikfranke2303 2 ปีที่แล้ว +1

    Amazing! Your Videos are so much comrehensible. I really enjoy watching!!!*_*

  • @solibozorgmehr6524
    @solibozorgmehr6524 4 ปีที่แล้ว

    Thanks for the explanation. Can you please make a video about consensus NMF clustering?

    • @statquest
      @statquest  4 ปีที่แล้ว

      I'll keep that in mind.

  • @daminithandele7237
    @daminithandele7237 4 ปีที่แล้ว +1

    Hi Josh! Can you please make a video on DBSCAN, if possible? Especially the parameter tuning part of it, I'm sure that would be of great help to lots of people.

    • @statquest
      @statquest  4 ปีที่แล้ว

      I'll keep that in mind.

  • @kanacaredes
    @kanacaredes 3 ปีที่แล้ว +1

    Hi Josh!! We need a DBSCAN tutorial please!!!!

    • @statquest
      @statquest  3 ปีที่แล้ว

      I'll keep that in mind! :)

  • @ardaugurlu8673
    @ardaugurlu8673 6 ปีที่แล้ว +2

    Good job mr josh.

  • @subhabrataghosh9831
    @subhabrataghosh9831 3 ปีที่แล้ว +1

    Excellent Sir

  • @yvonnemadegwa967
    @yvonnemadegwa967 6 ปีที่แล้ว +1

    Thank you very much! Can you teach software's? Like R-basic introduction, basics of how to arrange date with various commands?

    • @statquest
      @statquest  6 ปีที่แล้ว +1

      I have a handful of videos that teach you how to do certain things in R. They don't start at the very beginning, but I still go one step at a time. You can find these videos on the index page: statquest.org/video-index/

    • @yvonnemadegwa967
      @yvonnemadegwa967 6 ปีที่แล้ว

      @@statquest Thank you very much.

  • @ahmad3823
    @ahmad3823 9 หลายเดือนก่อน

    So, in each step, we have an upper triangle matrix of distances between current clusters and only combine the closest two and then repeat the process!? Silly in terms of computations!

    • @statquest
      @statquest  9 หลายเดือนก่อน

      noted

  • @giladshmueli5831
    @giladshmueli5831 3 ปีที่แล้ว

    looking through your stuff I unfortunately see no video about affinity propagation. I highly appreciate your videos, so I'd like to ask you to do this one, for me and everyone else, please!

    • @statquest
      @statquest  3 ปีที่แล้ว

      I'll keep that in mind

  • @charliekpeng
    @charliekpeng 2 ปีที่แล้ว

    How do you tell whether using Euclidean or Manhattan Distance would be more insightful without having to run both?

    • @statquest
      @statquest  2 ปีที่แล้ว +1

      Sometimes you know from how the data are generated (are you comparing commute times in manhattan? then use the manhattan distance) but usually you have to run both.

  • @huikianong1695
    @huikianong1695 3 ปีที่แล้ว

    Hi may I know how about the clustering of the column? Is it possible to cluster the column and row at the same time? Correct me if I am wrong, clustering the row meaning to group genes that have similar expression together from different sample ? Clustering column meaning to group the samples with similar gene expression?

    • @statquest
      @statquest  3 ปีที่แล้ว

      Sure! You can cluster both the rows and columns at the same time.

  • @2000starlines
    @2000starlines 7 หลายเดือนก่อน +1

    love the video:) I'm currently deciding whether to use hierarchical or k-clustering for my data though both work I really do not know which one is more suitable for protein abundance in two different biological conditions. If anyone has a suggestion I would be glad :)

    • @statquest
      @statquest  7 หลายเดือนก่อน

      Both methods are relatively subjective - so pick the one that gives you the better insights into your data.