Clusters using a Single Link Technique Agglomerative Hierarchical Clustering by Dr. Mahesh Huddar

[@Arf.78]

thank you so much sir....
apki wjah se machine learning ka paper bhut acha huwa...
love from Pakistan

[@MaheshHuddar]

Welcome
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[@salqarni6682]

You are my hero. Thank you so much send you love from Saudi Arabia ❤️

[@MaheshHuddar]

Thank you too!
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[@subhikshas4523]

Is distance between p3p4 0.16? why yor are putting as 0.13

[@vivekiyer9482]

Yes Even im getting 0.16

[@swetha3749]

same even for distance(p4,p5) i got 0.28 but in the video its given as 0.23

[@DesiCartoonsHindi]

same bhai...
Bhosadika sala sab isme galat value dalke rakhe sale ne sab videos galat hai .
MKC galat padha raha hai ekto kal exam hai

[@ShalinSingh-h2j]

Yeah I got the same - not entirely sure this example is right .

[@pragyadaksh7718]

What should be done if there is a tie when selecting the minimum distance?

[@sneha.tiwari]

Hello sir, I've one doubt, as in the first step, if we get minimum value at three places, then which two points will be chosen to form a cluster? For example, the min value is 2 and is between A,B and A,C and D,E Then in a first go, can we put ABC and DE as two cluster together?

[@leamon9024]

Thanks sir. Does hierarchical clustering be able to do feature selection?

[@raniaelrifai3337]

May God’s peace, mercy, and blessings be upon you. May God bless you, Doctor. I would like to ask you about the Self Organization Map Algorithm (SOM) part. How it works. I followed how the algorithm works mathematically. And how it works through the NN interface. But I have several questions: 1 I want to teach Anural to find a technology group by assembling the parts in a specific group close to each other 2. So I have a matrix consisting of 4 rows and 7 columns. I arrange it according to the largest weight for each row, then calculate the weight for each column and arrange it according to the largest value of the weights obtained. 3. And so it continues until there is no change in the values of arranging the rows and columns accordingly, as there is no change. This method is known as order rank clustering.
4. I want to benefit from this SOM method, other than that this method takes the closest distance from the method of calculating the Euclidean distance and classifies it into one of the clusters in the new layer, and so on. I would like to discuss it with you, if you please. In order to solve the ambiguity, and delegate this method to accomplish the problem that I have, regards

[@rutikbodkeacademy1247]

Thank you sir ....make more on this topic

[@MaheshHuddar]

Welcome
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[@leslieassabil2091]

Please do you have a video on complete linkage?

[@roboticsdesignforkidshyder3788]

thank you

[@techinfo89]

Excellent sir

[@techinfo89]

@@MaheshHuddar sir make a video on logistic regression

[@yogeshyewale478]

how to find distance between {p2,(p3,p6)} ?

[@ahmadelhourani367]

that depends on the type of link, for single link, you take the shortest distance from p2 either p2,p3 or p2,p6 as the distance between p2 and set of p3,p6

[@orhan4876]

Thank you!

[@swasthikbhat18]

thank you sir

[@MaheshHuddar]

Welcome
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[@sajanamethsarakulathunga243]

Superb❤

[@MaheshHuddar]

Thank You
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[@statisticalmethodologies7938]

Sir what formula did you use at 4:50 to merge P3 and P6 into a cluster (P3,P6) ?

[@samogx86]

In the matrix on the left, the minimum value is 0.10, so P3 merges with P6, the new cluster is (P3, P6) and since we are using Single Link we choose the minimum distance between distances P3, P1: 0.22 and P6, P1: 0.24

[@evo-star7850]

@@samogx86 According to your logic 5:35 while merging ( (P3,P6) , P4), ( ( (P3,P6) , P4) , P5) should contain 0.23. Can you explain why it's given 0.28?

[@samogx86]

@@evo-star7850 The new cluster is (P3,P6) , P4) and we need to find the shortest distance to P5, so we must choose between two distances given in the previous matrix: Distance (P3,P6) with P4: 0.37 or distance (P3,P6) with P5: 0.28. Now we know that shortest distance is 0.28.

[@ganiyudurosinmi2547]

@@evo-star7850 I think it is 28. I got 28 too not 23. It is square root of 0.0808

[@শেখোডটকম]

Superb teaching❤❤❤❤

[@MaheshHuddar]

Thanks and welcome
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[@SanataniRishu02]

What if P1 and P2 will be smallest 😶

[@nuf4027]

thanks

[@MaheshHuddar]

Welcome
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[@AnirrudhPrakhash]

7.50 distance between a point to the same point is zero.thats y we didn't take.

[@BoyAlone16]

Please sir what if for example the P1,P3 was the smallest distance can you explain which column am going to remove

[@evo-star7850]

P3 row and again P3 column(inverted L shape) will be removed and the lowest value of P1 and P3 will be written in new cluster P1,P3.

[@megamithra6910]

🔥🔥👌

[@MaheshHuddar]

Thank You
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[@sabertooth21]

Thank You Sir..

[@MaheshHuddar]

Welcome
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[@_ANUSHKADIVEKAR]

thank you!

[@MaheshHuddar]

Welcome
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