Introduction to Cluster Analysis with R - an Example

[@DineshKumarT1990]

Great tutorial!!...the way you explain is easy to understand...you should do more like this

[@bkrai]

Thanks for the feedback!

[@josebueno7602]

Please, how can I get the data utilities.csv? Thanks.

[@ramasamythirunavukkarasu6777]

Thank you so much Dr.B.Rai, I inspired your way of teaching even you in online, hopefully, every one enjoying your teaching

[@bkrai]

You are welcome!

[@factChecker01]

This is an excellent tutorial -- well presented and thorough. I followed along with my own application example (country healthcare per capita expenditure versus infant mortality rates of various types) and got very interesting results.

[@bkrai]

Thanks for comments and feedback!

[@sebastiansocianu5441]

5-star explanation. thank you! Very much recommended for beginners and intermediate R users. You got a new follower!

[@bkrai]

Awesome, thank you!

[@ArcenisRojas]

Great tutorial. I really like how you stuck to explaining the steps through a practical application. Thank you for this.

[@bkrai]

Thanks for comments!

[@rarosification]

My goodness, this video is so complete, and clearly explained with details of the script... Thank you so very much... 100 points to you...!! You have a new fan...

[@bkrai]

Thanks :)

[@karoargote]

Really thank you so much!!! The best tutorial on this topic!!!

[@bkrai]

You're very welcome!

[@kanikalungani]

If i had a thousand likes you would have received them all sir. Love the way you have explained and covered the concepts

[@bkrai]

Thanks, I’ll consider it 1000😊

[@stephenhobbs948]

Excellent explanation and code. I took the Johns Hopkins data science course, and clustering was part of the course. This video really helps explain the concept.

[@bkrai]

+Stephen Hobbs thanks 👍

[@markshanks9142]

This is truly an excellent, clear and concise tutorial. You covered a lot of topics in a short amount of time. I will be watching your other videos. Well done!

[@bkrai]

Thanks for your comments and feedback!

[@rupeshbharadwaj]

Great tutorial! You are really helping a lot of people like me, and the best part is- drama, background music etc are completely missing unlike many other tutorials. Also saw some bhojpuri songs :)...thank you sir!

[@bkrai]

Thanks for comments and feedback!

[@sarahroffe2142]

This is a brilliant tutorial which is easy to understand and follow.

[@bkrai]

Thanks for comments!

[@janelutken9818]

Thank you so much. This was easy to follow and I did my own analysis as we went along with almost no trouble. This was a breakthrough video for me.

[@bkrai]

You are welcome! For more detailed presentation, you may refer to: kzbin.info/www/bejne/paXNiHaXgsiJl6M

[@archeops.]

Fantastic explanation! I followed along with a different dataset and it worked perfectly! Great work!!

[@bkrai]

Thanks for comments!

[@harikamacharla7005]

Wah!!! how could u explain it so well!! Great job.

[@bkrai]

Thanks!

[@emiltsenov7853]

Hi Bharatendra, this is an excellent tutorial - the first one that worked for me. Great effort, keep up the good work!

[@bkrai]

+Emil Tsenov Good to know, thanks for feedback!

[@ahmetcandemir7032]

Very good tutorial ! impressively well explained. Thank you

[@bkrai]

You are welcome!

[@arnab_jana]

After a long time, I have seen such a good tutorial. Thanks, for your effort

[@bkrai]

+Arnab Jana Thanks for the feedback!

[@tradingtraveller05]

Thanks for such wonderful explanation. By the way, I was working on a similar dataset, and apply didnt work for me. Although I removed all character vectors, but still the numeric vectors were returning 'NA'. I applied sapply and it solved the purpose. Thanks again!!

[@bkrai]

Good to hear!

[@kapilrana1153]

Great Explanation! Thank you Sir For this Video Lecture I will be watching your other videos.

[@bkrai]

Thanks and welcome!

[@abdulkhader101]

You are a great teacher sir, you are really awesome

[@bkrai]

Thanks for comments!

[@mwambakapambwe2382]

Fantastic presentation. Very helpful

[@bkrai]

Thanks for comments!

[@kishoreyarramshetty2930]

Good Job in explaining the content along with code..

[@kishoreyarramshetty2930]

can u provide us the link to download the dataset in this video to run the code.

[@bkrai]

Thanks for comments!

[@bkrai]

For data, there should be a link below this: kzbin.info/www/bejne/paXNiHaXgsiJl6M

[@nafinks6081]

Excellent tutorial! very easy to grasp.

[@bkrai]

+Nafin Ks thanks for the feedback!

[@bassamal-kaaki3253]

Lovely explanation:) easy to absorb.

[@bkrai]

Thanks for comments!

[@Aminah6623]

Wow. This was extremely helpful. Thank you.

[@bkrai]

You're very welcome!

[@saikrishna2589]

Thank you for wonderful explanation. Appreciate your help with these amazing videos

[@bkrai]

Thanks for your feedback!

[@jonathanrhein7553]

Hi Bharatendra, great video - really helpful! Everything goes well until the point of doing the scree plot, I am getting: > withinGroupSumOfSquares = (nrow(normNum)-1) * sum(apply(normNum, 2, var, na.rm=TRUE)) > for(i in 2:20) withinGroupSumOfSquares[i] = sum(kmeans(normNum, centers=i)$withinss) Error in do_one(nmeth) : NA/NaN/Inf in foreign function call (arg 1) > plot(1:20, withinGroupSumOfSquares, type="b", xlab = "Number of Clusters", ylab = "Within group SS") Error in xy.coords(x, y, xlabel, ylabel, log) : 'x' and 'y' lengths differ Can you help me? Thank you.

[@jonathanrhein7553]

someone has deleted my comment...

[@bkrai]

+Jonathan Rhein Not sure what's causing the error you got. May have something to do with data. I ran my data using the code you have, and everything seems fine.

[@bkrai]

+Jonathan Rhein I still see your previous comment.

[@rosestube1233]

Thank you for this tutorial! it's amazingly easy to follow and thanks a lot for the script/file

[@bkrai]

+Roses Tube 👍

[@kandreitapomen]

Great tutorial. Thank you very much!

[@bkrai]

+Kandreitapomen 👍

[@EduardoFrancoChalco]

Really great tutorial, thank you very much!

[@bkrai]

+Eduardo Franco Chalco 👍

[@EduardoFrancoChalco]

Would you please send me the scrip and data? email: [e-mail]

[@saikatkar547]

thats really excellent explanation!

[@bkrai]

Glad it was helpful!

[@gulapakarthik3864]

This is really Amazing...Thank you so much 😎

[@bkrai]

You are welcome!

[@omkarsingh6060]

Amazing...Really impressed

[@bkrai]

Thanks for comments!

[@khushboobegwani1612]

Thank you so much sir for informative video. You really made it easy.

[@bkrai]

Thanks for your comments!

[@metalhealth14]

this is a really great detail thank you! I appreciate the detailed guidance into understanding and checking cluster membership

[@bkrai]

It's good to hear your feedback! Thanks

[@prashantmishra2094]

nice tutorial Sir. Keep making such videos

[@bkrai]

Thanks for comments!

[@alicelatimier3133]

Thank you so much for your amazing videos, everything is so clear and practical :) From a french research in cognitive science, I have one tricky question for you : i would like to find the best classifier/cluster analysis for repeated measures dataset (i.e., multiple repeated measures for one subject on the same features, as this is the case in experimental psychology research for example, or in longitudinal studies). Best

[@bkrai]

You can look into this link: kzbin.info/aero/PL34t5iLfZddvMPAl1TzHJ_GjQcD3s6w_Z

[@txigual]

Thank you so much, very useful video.

[@bkrai]

Thanks for comments!

[@fredpoole6373]

Great Video! Look forward to more videos!

[@bkrai]

Thanks for comments! For more machine learning videos you can use this link: goo.gl/WHHqWP

[@zhuziyan9454]

dear professor, I am so lucky to know you. could you also update full tutorial about using rmd and advanced model like hmm? Thank you and wish you have a great day

[@bkrai]

Thanks for the suggestion, I've added this to my list.

[@asifjeelani1215]

thank you sir, very well explained

[@bkrai]

Thanks for comments!

[@thejuhulikal6290]

sir please make the video on this K-mode also, that would be great to understand both topics and comparison

[@bkrai]

Thanks, I've added it to my list.

[@betzthomas9693]

Thank you Sir for the tutorial.Please explain if there is any package is R to identify on what basis clusters are grouped from the data we provide.

[@bkrai]

Refer to the averages for each cluster and all variables.

[@liamhannah6325]

This was really helpful THANK YOU! Make more! I would love it if you showed us how to do Latent Class Analysis in R, its not obvious right now

[@bkrai]

Thanks for comments and suggestion!

[@Nit1601]

THE BEST !!! Could you please advise, do we need to do anything else to normalize if we are dealing with Binary columns (0,1). Thanks !

[@bkrai]

We should exclude such variables.

[@ssundaraju]

Very Informative, great slides and explanations. The delivery and presentation was good. I will be viewing other videos produced by Edureka. Some suggestions, show more examples. Present the limitations and god fit scenarios for K-means clustering.

[@bkrai]

Thanks for comments and feedback!

[@sajidurrahmannafis8476]

Best tutorial in the internet. I have one question: why are using euclidean distance then again complete linkage? I thought we need one distance measurement technique. I will be really grateful if someone can clarify. My questions answer may help others also. Thank you.

[@bkrai]

You can refer to this more recent one: kzbin.info/www/bejne/paXNiHaXgsiJl6M

[@sajidurrahmannafis8476]

@@bkrai Thank you sir. I am a big fan of your teaching. I am also a research assistant in US. Thank you for your amazing lectures!

[@sajidurrahmannafis8476]

@@bkrai Thank you. I got the answer to my question from your new cluster video lecture.

[@bkrai]

Thanks for the update!

[@bkrai]

You are welcome!

[@biswadeepdas5528]

sir, it is quite good. I would really appreciate if you upload more videos .

[@bkrai]

+biswadeep das thanks for your feedback! I'll definitely create more such videos.

[@hridayborah9750]

yes all your videos are helpful. Could you prepare a tutorial on machine learning in the tidy verse.

[@bkrai]

I've added it to list of future videos. Thanks!

[@thejuhulikal6290]

Sir please do the vedio on PAM algorithms!

[@bkrai]

Thanks, I've added it to my list.

[@tahzeebfatima3121]

Thanks for the informative video. May I please know how to deal with dichotomous variables along with continuous variables in the data if we want to include both in one cluster analysis, how do we do it please?

[@bkrai]

This link has more cluster analysis topics: kzbin.info/www/bejne/paXNiHaXgsiJl6M

[@DeepeshSinghAndroid]

Hi Mr. Rai, great tutorial. Thanks for your effort. Just wanted to understand more about these 2 methodologies. Why and when we apply different methodologies i.e. K means and Hierarchy. It will be great help if you can make separate videos for the same. Also, as lots of people requested for data set and you have already uploaded to Dropbox, could you please share the link in your description for everyone's benefits. Thanks again :)

[@bkrai]

Initially we try all methods and finally choose the one that seems more meaningful for the dataset used. It's difficult to say which method will work best beforehand. Also thanks for your feedback and suggestions.

[@TusharLapani]

Thanks Bharatendra. Can you please upload video of how to performe clustering when the dataset has numbers of numerical attributes and categorical attributes. In this video you are eliminating categorical attribute. What would you have done if your dataset has 10 numeric columns and 8 categorical data. Appreciate your knowledge contribution.

[@bkrai]

+Tushar Lapani For cluster analysis you must have quantitative variables. You can use categorical variables after cluster analysis to see if they show any pattern with identified clusters and use it for characterizing the clusters.

[@desisto007]

Thank you so much! Very well explained. I would like to ask you if I still can use the Euclidian distance to find the closest elements of a cluster center, even if I use a dimensionality reduction approach (such as PCA, T-sne) that uses probabilities to arrange clusters in 2 dimension before using K-means.

[@phediasdiamandis2441]

Great Video. Congrats

[@bkrai]

+Phedias Diamandis thanks for the feedback 👍

[@mallorywright1453]

Do you have any examples of validating a cluster analysis using LPA?

[@bkrai]

I'm adding to the list of future videos.

[@javzmaatsend3785]

Thank you, Very easy

[@bkrai]

You are welcome!

[@stephravelo]

This is a very informative video. I hope you would have a repository github of your data so that we can play around with the script you used.

[@bkrai]

Here is the link: github.com/bkrai/Top-10-Machine-Learning-Methods-With-R

[@shubhasmitasahani1738]

Hello Sir, do you have any video on latent class clustering in R? Please share...Looking forward.

[@bkrai]

Not yet, but I'm adding this to my list for future. For clustering related videos, you may refer to this link: kzbin.info/aero/PL34t5iLfZddvMPAl1TzHJ_GjQcD3s6w_Z

[@zhuziyan9454]

could you please explain why subtracting the first variable by [,-c(1,1)] rather than[,-1]? Thank you

[@bkrai]

Both work fine. You can use it if you need to remove more than one variable.

[@sanjayh3897]

Excellent tutorial Bharatendra ! Do you have any example to share for Overlapping clustering - would appreciate it. Thanks !

[@bkrai]

There are 52 datasets where clustering can be applied in the link below: archive.ics.uci.edu/ml/datasets.html?format=&task=clu&att=&area=&numAtt=&numIns=&type=&sort=nameUp&view=table

[@mariaamithapennington3737]

Thank you so much for the tutorial. It is extremely helpful. But my question like the other is that it would have been very kind of you if you would have linked your data set too. Thanks!

[@bkrai]

You can get it from here: kzbin.info/www/bejne/paXNiHaXgsiJl6M

[@mariaamithapennington3737]

@@bkrai Thank you very much! Appreciate it! :)

[@bkrai]

You are welcome!

[@tabasummirza8638]

great tutorial.please tell me how to label he clusters

[@bkrai]

You can come up with appropriate names for the labels by looking at averages for each cluster and each variable.

[@santosacosta4645]

Thank you very much sir. Question: using Within group SS plot (min 14:39), isn't the optimal number of clusters 5? the variability from 4 to 5 seems very significant. Please let me know.

[@bkrai]

This data has only 22 companies. As we increase number of clusters, number of companies in some clusters becomes really small, to the extent that a cluster may contain just one company. So the choice of 'k' should also consider this aspect.

[@rithishvikram1759]

nice explaination sir!!!!! thank you so much ....great respect ....sir if you would pls attach concern datasets with a video ...thank you once again

[@bkrai]

send your email id

[@rithishvikram1759]

[e-mail]

[@bkrai]

all set.

[@rithishvikram1759]

thank you so much sir

[@tanmay094]

Nice and informative tutorial sir. I am performing hierarchical clustering on my dataset with 10 variables and 200 observations. But the output is not very interpretable. Please suggest how can I make it more interpretable. Thanks.

[@bkrai]

You can explore other clustering methods and if they provide better insights. Here is the link: kzbin.info/aero/PL34t5iLfZddvMPAl1TzHJ_GjQcD3s6w_Z

[@tanmay094]

@@bkrai Thanks, sir. I have one more query. I want to do cluster analysis on PCA. Can you please suggest a good reference tutorial for doing that?

[@bkrai]

This approach will work fine.

[@shezamalik7918]

hello sir, great tutorial, you're a life saver for marketing analytics course! I have a question regarding Scree plot code: wss

[@bkrai]

it tries 1 to 20 clusters.

[@shezamalik7918]

@@bkrai oh right, thanks alot! Can you also tell how do we deal with gender variable for clustering? What im doing is mutating a new var thats 1 and 0 instead of male and female. I then convert that to numeric variable. And then i do the usual process. Is this correct?

[@bkrai]

For clustering, we should use only numeric variables.

[@shezamalik7918]

@@bkrai so how should i deal with gender? Its an important variable in marketing for ad targeting etc

[@bkrai]

you can put that on Dendrogram after clustering to see if it shows any pattern.

[@anigov]

Dear Sir..thank you for the time & effort that you have put in to make this wonderful video tutorial. I have a query. At 12:27 , how are the original average values displayed even though member.c is used which is obtained through a series of calculations using the normalised data? Why did not you use PCA to decide the no. of clusters for kmeans? Regards Aniruddh

[@bkrai]

In the 2nd aggregation line, note that I've used utilities. That's the reason we can display original values. In the 1st aggregation, z was used. Also, here focus was on clustering, so pca is not used.

[@anigov]

Thank you

[@mfkalabdullah6966]

Sir, Do you have more videos on clustering? Also, can I contact you in the future regarding clustering because I'm doing a research using data mining clustering?

[@bkrai]

There is a playlist on clustering: kzbin.info/www/bejne/paXNiHaXgsiJl6M

[@Guavarosa]

Please can you give me a hint? I want to give as input the initial centres for kmeans clustering. I just do not manage to select these points out of my dataset. Thank you in advance for your help!

[@bkrai]

Why do you need that? The algorithm should automatically take care of finding the best clusters.

[@Guavarosa]

@@bkrai Because I try to correlate my clusters to the physical problem. That is why I was wondering if I can give initial centres as in case of software Origin Pro. I appreciate your answer.

[@rohanshetty1016]

Sir your video lectures are really awesome! Excellent Tutorial! Can you please share the csv file used for cluster analysis?

[@bkrai]

send me your email id.

[@ramp2011]

Great tutorial. Thank you... How do you handle categorical variables for clustering? In this example looks like you removed the 1st column that happened to be a factor variable. Can you please post the data file used in the comments as well if possible? Thank you

[@bkrai]

Cluster analysis only works with quantitative variables. During the analysis you may note that we calculate distances, which we cannot do with categorical variables. But after finalizing number of clusters, you can plot dendrogram with a categorical variable to see if there is any obvious pattern or not. For data, send email id.

[@Jorge-vp7of]

you can use K-modes to do clustering with categorical data

[@medardkafoutchoni6511]

Thank you dear Sanchez. What about mixed data (i.e. including both numerical and categorical variables)?

[@vivekwilliam3370]

[e-mail]

[@keeninterest8889]

Sir, Can you please tell me whether it is necessary to do normalization to qualitative data?

[@bkrai]

No you don’t need it for qualitative variables.

[@keeninterest8889]

@@bkrai Thank you sir

[@niv2419]

Hello sir, as always your videos have been very helpful and thank you for this video too. Also, I wanted to know if there is a way to improve between cluster distance? If so can you please let us know? Thank You!

[@bkrai]

You can increase or decrease number of clusters and see which one improves between cluster distance.

[@shruthihariharapura]

hi, excellent tutorial, it helped me a lot, can you help us in implementing density based clustering in R. Feeling difficult in implimenting

[@bkrai]

Thanks!

[@rezaamirahmadi6013]

Thanks , How can I use fuzzy k-means (FKM) to impute missing in R ?

[@rinoypaultharu5071]

Great tutorial, it really help for my analysis. Im having some douts, in that while silhouette calculation, whether we need to check average silhouette value, or which value we have to check to find out the number of clusters. Please help me with that. In your analysis what is the silhoutte value for k=3, where it is showing on that plot? Second while calculating my Euclidean distance, i have 40 observations, so it is not showing complete rows of Euclidean matrix, so is there any other way to obtain the complete matrix

[@im_karamo1907]

Thanks for the video... how can we get the video to practice on? Thanks again for the video

[@bkrai]

If you need data, send me email id.

[@im_karamo1907]

@@bkrai my email ID # [e-mail]

[@bkrai]

all set.

[@betzthomas9693]

Can you please explain in K means clustering(Scree plot).What is the idea behind wss calculation

[@bkrai]

wss is within sum of squares that captures within cluster variability. When wss is low, then cluster formation is good.

[@betzthomas9693]

Thank you @@bkrai

[@aks1008]

Sir how to remove multicollinearlity in cluster analysis as it is an unsupervised algorithm..there is no dependent variable..

[@bkrai]

Multicollinearlity is a problem only for regression models. For cluster analysis it not an issue.

[@sathiarams7273]

Nice video and beautiful explanation... where can I download this data set utilities. pl help

[@bkrai]

send me your email id.

[@springANDstorm]

Sir, how to interpret the between SS/total SS value? In your example, it's 36% . How should that be interpreted?

[@bkrai]

Between SS captures variability between clusters. When it increases, it indicates better clustering because within cluster variability will come down. Elements within a cluster should be closer to each other whereas elements between clusters should be further away for a good cluster formation.

[@springANDstorm]

@@bkrai thanks Sir.

[@niv2419]

Hi! Thank you so much of making this blog! Can you please make a video on feature engineering in R? Thank you!

[@bkrai]

Here is the link: kzbin.info/www/bejne/jHalkqtojLKVe6M

[@azfersaeed1602]

Great video man! Thank you very much for posting :). Could you show cluster analysis using more than 2 variables?

[@bkrai]

+Azfer Saeed thanks for feedback! In the example we have cluster analysts with 8 variables. However for scatter plot we use two variables at a time.

[@azfersaeed1602]

+Bharatendra Rai You are correct...sorry for the incorrect semantics. At 2:15, you mention that broadly, there are 3 clusters but they are based only on 2 variables. Is there a way to create clusters based on more than 2 variables?

[@Bidushranjan]

sir can u make a video about D2.dist function of biotools packages to calculate d2 distance matrix easily and tochers method of clustering which is mostly used in agricultural research

[@bkrai]

Thanks, added to my list.

[@gambhiraogirish1710]

Thanks for great explanation sir. May I have data set for practice please. Thanks again sir.

[@gambhiraogirish1710]

my mail ID is [e-mail]

[@bkrai]

all set.

[@vinzkyvijayaraj4035]

Thank you!

[@bkrai]

You're welcome!

[@chitralalawat8106]

Does mclust also required normalization of data?

[@bkrai]

It's always better to do normalization.

[@chitralalawat8106]

@@bkrai I have many files which I want to concatenate..should I concatenate and then normalize the data or should I normalize and then concatenate?

[@bkrai]

You can first concatenate.

[@chitralalawat8106]

@@bkrai Are you sure?

[@sudhakarbabunynavarapu8133]

Could you please send the data files for the practice what datafiles used in the tutorial.

[@bkrai]

email id?

[@machinelearningzone.6230]

HI Sir, How do we assign the clusters to new data points, like if we have a new data set but use the same model. Regards Gourab.

[@bkrai]

You can develop a prediction or classification model with cluster as independent variable.

[@machinelearningzone.6230]

@@bkrai Thank you . Do you mean that we can develop a classification model using the clusters labels as classes?if so,then how do we take into account the distance parameters like eucledian or taxi cab etc..

[@bkrai]

You don't need that as it is already baked into the clusters.

[@harishnagpal21]

Nice video as always. I have couple of questions. In K means cluster example, if we want a list as per the three clusters, how do we tag that. 2nd query, I have a data set of 100000 insurance customers having customer ids and their policy Face amount. I want to divide them in cluster ( say 5 cluster) and also want to know which customer comes in which cluster (same query as first) so that I can target them for a campaign. How do we do that and which clustering technique to use? Thanks in advance.

[@bkrai]

You can use something similar to kc$cluster that I've used at around 16:30 time point in the video.

[@harishnagpal21]

Thanks

[@tanmaygawade1068]

hello sir!! actually wanted to know how to perform clustering on PCA generated scores in r and how to compare the cluster size for both.

[@anmolsmartkid]

quite a descriptive one..please share the csv file..ill be obliged.

[@bkrai]

Link below this: kzbin.info/www/bejne/paXNiHaXgsiJl6M

[@thejuhulikal6290]

Hello sir, please upload a video on Qualitative comparative analysis!! thanks again sir

[@bkrai]

I've added it to my list, thanks!

[@arunsoni3280]

Which software does it run on ?

[@bkrai]

If you are looking to get started with RStudio, you may find this link useful: kzbin.info/aero/PL34t5iLfZddv8tJkZboegN6tmyh2-zr_T

[@abhiagni242]

Thanks for the video sir,,, .... can u Plz share the link to the dataset used

[@bkrai]

email id?

[@jyoti9426]

How to plot clusters if I already know the affiliations of the nodes?

[@bkrai]

Not sure about your question, but you may try this: kzbin.info/www/bejne/rX3YY2Rpf7CZpLM

[@maryamaziz5064]

would love to try it on my own

[@bkrai]

Thanks!

[@sayedyavar3752]

i want to remove multiple columns from my data set just like you removed the company. what code should I use?

[@bkrai]

let's say tou want to remove columns 2, and 4 from 'data' that has 5 columns. Then, data1