L32: K-Means Clustering Algorithm | Solved Numerical Question 1 (Euclidean Distance) | DWDM Lectures
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- เผยแพร่เมื่อ 2 ต.ค. 2024
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In this lecture you can learn about K-Means Clustering Algorithm - Solved Numerical Question 1(Euclidean Distance) in Data warehouse and Data Mining(DWDM) Course. Following topics of Data warehouse and Data Mining(DWDM) Course are discussed in this lecture: K-Means Clustering Algorithm - Solved Numerical Question 1(Euclidean Distance). This topic is very important for College University Semester Exams and Other Competitive exams like GATE, NTA NET, NIELIT, DSSSB tgt/ pgt computer science, KVS CSE, PSUs etc.
K-Means Clustering Algorithm - Solved Numerical Question 1(Euclidean Distance)(Hindi)
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Bhai 4 saal se tere videos dekh raha. Tune meri engineering paar krwa di....Thanks
bally bahi tune tareef ki hy k pathar mara hy😂
@@syedawrites547 😂😂😂
9:44 the value of ED of Row 4 for cluster 1 will be square root of 52 not 40 ......
yes its subtracted value will be 4 not 2
@@mohamedsameerahmed5132 yeah agree
Agree
that is what am saying
my ans is c1{1,4,5,6,7,8,9,10,12}
c2{2,3,11}
it is different from yours
so can you please check if my answer is correct or not
please help me out for the same
Yes your answer is right. My answer is same as yours.
bro he did a little mistake for row 4 where finding for c1 (there should 4 square = 16 and fills 2 square = 4) so don't worry
Mine too
C1=16.12
And
C2=14.21
In my case
Thank you so much very helpful
The value of C1 for Row 4 is 7.21
im relieved now
Yes
bhai isne 72-68= 2 bola
For each row, if you change the centroid then the iteration will be near to infinite. First, calculate ED for all then calculate the new centroid.
true
Okay. This is wrong. You are assuming that row 1 and row 2 fall in different clusters. What if they don't??? What if they are meant to be in the same cluster??? This method is not correct
Nope this is correct..In the initial step, the Euclidean distance of one cluster from itself is obviously lesser than the euclidean distance of the same cluster with the other cluster.
WRONG METHOD. The centroid is calculated after classifying given points into appropriate clusters in every iteration.
He reduced the set to only 4 dataset for calculation ease. Otherwise, it would have be a very long video.
Don't update cluster centroid after every assignment update it after a whole iteration (all assignments in one iteration is complete)
This will be when you are working with simple datasets, where you first add everything to the cluster and then calculate mean at the end.
Both methods are fine. They have their own advantages and disadvantages but they both are correct
Hme degree college ne di h aur gyan aapne thank you sir g
wrong explanation bc
When equlian distance is equal then how will i find the Cluster 🥺🥺
someone plz explain me that how row 5 goes to c1 when distance of c1 is 2 and c2 is 19.1
this seems little bit confusing......because some reasons are not explained...why to do that??
row 11 goes to c2 nt c1
Yup you are right, row 11 will go to c2.
Yes
Also For Row 4, C1 value is 7.21
@@akshitmehta4139 it's calculation mistake but in this it doesn't effect it's final result
yes right
Thankyou sir ... It's very helpful for semester exam.. 😍😍
Wrong.. 1st calculate Eucladian distance of all values against 1 fixed centroid value. Then take mean and find the new centroid. Repeat it till mean value does not change in 2 consective iterations.
Solution given in video changes mean value in each step which is against the rule of iteration.
Thanks
68-72 = -4 not -2 correct it video timing 9.36
u r right
u are right bur phir bhi select C1 me ho hoga.
Should we change centroid every time a new item is kept in the cluster?
Yes
no, this procedure is not correct.
R11 belongs to C2 because of E.D of C2 on R11 is less.
same
Same here too
One suggestion is that solve this problem at the last of paper because it will take most of time 😃
Sir After Finding New Centroid c2 E>D of c1 the Value is Wrong your Value answer is 6.32 and My answer value is 7.21.
Yes right
plz help,
Assume you are given n points in a D-dimensional space and an integer k. Describe the k-means ++ algorithm for clustering the points into k cluster
?
nice and easy explanation
6:59 what if both values are same
the centroid value shouldn't be change. every step. first we have to find with the same centroid for the whole at once. the question will give how many iteration you have to perform. so change the centroid after each iteration only
If euclidean distance for both the clusters are same , then in which cluster will they fall
Bro are you solved??
thanks sir but aap bata sakte hai kya (68-72)sq kaise 2 ho gaya. 16 hota hai sir Full Root hai naa sir
. Still explain karne ke liye thanks.
Concept is wrong. Centroid should not be calculated at every row. Centroid of A,B,C,D row should be (A+B+C+D)/4 while using the method in video it comes to A/8 + B/8 + C/4 + D/2. which is totally wrong. Try yourself with A,B,C,D as 0,0. 2,0. 0,2. 2,2.
Sir, if we randomly take the initial parameters then the clustering will not be the best solution. Instead, we can take one parameter as the initial parameter and from that, we can calculate the second initial parameter such that the difference between the first initial parameter is maximum with the second initial parameter(the one which is calculated). But anyways a great lecture.
No. This doesn't solve it. This entire video is wrong. The real k means algorithm is an iterative approach. You have to come back to all the rows again in the 2nd iteration and then 3rd etc till the cluster you get in consecutive iteration is same
The algorithm that you are talking about is K means++
Bro youre amazing ... . . . . . .
sir ji 8 number ka aata hai hamare yaha voh bhi subquestiob mai
K-medoids clustering algorithm with solved problems ???
Sir your explanation of every lecture is excellent and very useful👍👍👍👍👍👍👍
Kiya Sir ji ,Pura solve karna chahiye tha na Hum logo ko kaha itna aata hain ...aata toh thodi na aapka video dekhta...
Not a valid method as not getting correct answers using it. I learned from book directly where centroid need to be calculated at the end of whole iteration and repeat the itemset cluster classification until reach to the no change state!
Cluster the following eight points (with (x, y) representing location) into three clusters.
A1(2, 10), A2(2, 5), A3(8, 4), B1(5, 8), B2(7, 5), B3(6, 4), C1(1, 2), C2(4, 9).
The distance function is Euclidean distance. Suppose initially we assign A1, B1, and C1 as the center of each cluster, respectively.
(a) The three cluster centers after the first round of execution and
(b) The final three clusters?
Ans:
(a) After the first round, the three new clusters are:
(1) {A1},
(2) {B1, A3, B2, B3, C2},
(3) {C1, A2},
and their centers are
(1) (2, 10), (2) (6, 6), (3) (1.5, 3.5).
(b) The final three clusters are:
(1) {A1, C2, B1}, (2) {A3, B2, B3}, (3) {C1, A2}.
Exactly
6.32 is Wrong Its 7.21 SQRT(36+16) -> 68-72 = -4 and not -2
please do not follow this method, i lost my marks following this.
suggest a method then
Sir couldn't find Machine learning whole Playlist from lecture 1😢 please help sir 🙏
Sir apne R4 meh c1 ke jo pts aye h unhe apne le liya or R5 meh agr meh unhe leta hu toh vo C2 meh ja rha pr apne C1 meh likha hain
Iska mtlb bakiyo meh apne as it is hi use kita h
fir R4 meh apne pts kyu liye thee bina uske vo C1 meh nhi ja rha thaaa
i think it is not 6.32 in r4 it is 7.211
sir apne 6.43 nhi 7.21 value ban rha hai kindly make sure
How can you initialize first two rows into two different clusters? What if they are meant to fall in single cluster?
It is done at random. If they are meant to be in same cluster they will eventually fall into same cluster.
@@Joyddep what do u mean eventually??? The method shown in this video is based on a single iteration. And you get the final answer. You are not coming back to the 1st and 2nd rows again.
You're right. This video is absolutely incorrect. He is assuming the placement of row 1 and row 2 in different clusters
Can row selection be random?
The concept is totally wrong in both k-means videos. We do not update the centroids unless we have gone through all the points. After that, mean of resultant clusters are found and they are considered to be the new centroids and this process is repeated again and again till we get no new clusters.
Concept is wrong. Centroid should not be calculated at every row. Centroid of A,B,C,D row should be (A+B+C+D)/4 while using the method in video it comes to A/8 + B/8 + C/4 + D/2. which is totally wrong. Try yourself with A,B,C,D as 0,0. 2,0. 0,2. 2,2.
Both the concepts are correct. The approach sir discussed is called incremental centroid updation and it resolves some of the problems related to the traditional method you are talking about. Both the methods are correct.
kindly keep the paper a bit up ...the last tupple isn't clearly visible in most of the videos
Changing the centroid even if the cluster is not including a value !!!!
Why u r changing the centroid of the cluster which is not including a row ?
row 4 of c1 ans is 7.21
Thanks a lot sir
Pen konsa use krte ho yeh batana
App aake mera exam de skte ho?
A lot of confusions.
Wrong mathod
Great explaination ❤️
Sir k medoids clustering algorithm with solved problems
12 sayad c2 me aaiga
Is this 2d kmeans clustering
Great explanation sir keep uploding different videos of various methods of various subjects. Your videos really help us to understand the concept. Thank you sir.
Bhai yeh smjhaya hai
Which pen is used by sir?
row 3 ke c2 me 4.47 value aaegi
Why changes in the order of rows are changing the number of value for each cluster. original it is C2= 2,C1= 10, but when i changed order it's count is C1=1 and C2=11. Can someone explain, please?
11 row k2 m jati hai🤦♀️ 😂
Thank you it is very helpful and please keep making such kind of videos
Great explanation
C1 kabhi change nai hoga and only c2 change hoga???,
how many itertaions needed??
Isnt there any video on medoid clustering algorithm??
This method is wrong according to mumbai university procedure.
This is the only method brother !
Ask university to watch youtube videos !
ROW 7 goes to C2
Centro for row 4
What if tuple 1,2 fall in same custer? Illogical explaination.
Check my comment.
@@adityapanchal5803 which comment??? There is no explanation for this. You cant simply put the first 2 values in different clusters. If this method was iterative then you would come back to the 1st and 2nd row and then they would fall in the same cluster or remain different. However in this video its not iterative so you are never coming back to the 1st and 2nd row therefore you don't know if they are in the same cluster or different
simply amazing india
Thank you Sir🙂🙂🙂
Grateful
good efforts
Sir please sahi calculation kare.
Present sir saraswati dhodi
Row 3 mein 2 kaise aaea
why row 3 will go to c2?
Integration video please msbte
Hello Everyone
Very well explained! 👏
Breath out itna q kar rha...
keep uploading more examples
You are doing wrong calculation ,correct it and repost
who needs calculation brother just understand concept
K medoid ka problem upload karo sir ji
Tq sir
Thanks
Sir wo pen kaha se li
Posted wrong video, simply amazing india, calcualtion is wrong
thanks sir
Foul video.....plz correct both calculation and concept .
row 4 me calculation mistake hai...
Soperb
👍😁
Thanks bro
Sir apni photo to dikhado ...kisi din ......
thank you Easy Engineering classes ....