Hi Thank you for your comment every observation will be stamped into a particular cluster. Suppose your Cluster Object is KM then you can print(KM$cluster) and then you will be able to see which observation is assigned to which cluster. Furthermore you can add this cluster stamping as a column to your existing data frame. In order to elucidate my aforementioned explanation I will attach a link which has a code for cluster identification for each observation :- www.geeksforgeeks.org/k-means-clustering-in-r-programming/
@@easyml1234 Hi, I am confused between the representation of clusters obtained in the video and the geeksforgeeks link you have provided in this comment. I am unable to figure out which one I should be using and for the video I see that when the points in either cluster do not overlap it is a valid cluster formation. But in the link example they have created 3 clusters and they are overlapping but still it is considered correct. Could you explain how? I want to find the parameters from my sample sheet being clustered in case of 2,3,4 clusters (which are valid in my case). I wish to find out on the basis of which parameter, R has categorised my samples. Also, the command in the link is not giving me the p-value and kappa as shown in the example. I would highly appreciate any leads on this. I need it urgently for my work. Thank you :))
@@easyml1234 Hi, I am confused between the representation of clusters obtained in the video and the geeksforgeeks link you have provided in this comment. I am unable to figure out which one I should be using and for the video I see that when the points in either cluster do not overlap it is a valid cluster formation. But in the link example they have created 3 clusters and they are overlapping but still it is considered correct. Could you explain how? I want to find the parameters from my sample sheet being clustered in case of 2,3,4 clusters (which are valid in my case). I wish to find out on the basis of which parameter, R has categorised my samples. Also, the command in the link is not giving me the p-value and kappa as shown in the example. I would highly appreciate any leads on this. I need it urgently for my work. Thank you :))
hey can you tell me which point lie on which clusters
Hi Thank you for your comment every observation will be stamped into a particular cluster. Suppose your Cluster Object is KM then you can print(KM$cluster) and then you will be able to see which observation is assigned to which cluster. Furthermore you can add this cluster stamping as a column to your existing data frame. In order to elucidate my aforementioned explanation I will attach a link which has a code for cluster identification for each observation :- www.geeksforgeeks.org/k-means-clustering-in-r-programming/
@@easyml1234 Hi, I am confused between the representation of clusters obtained in the video and the geeksforgeeks link you have provided in this comment. I am unable to figure out which one I should be using and for the video I see that when the points in either cluster do not overlap it is a valid cluster formation. But in the link example they have created 3 clusters and they are overlapping but still it is considered correct. Could you explain how? I want to find the parameters from my sample sheet being clustered in case of 2,3,4 clusters (which are valid in my case). I wish to find out on the basis of which parameter, R has categorised my samples. Also, the command in the link is not giving me the p-value and kappa as shown in the example. I would highly appreciate any leads on this. I need it urgently for my work. Thank you :))
@@easyml1234 Hi, I am confused between the representation of clusters obtained in the video and the geeksforgeeks link you have provided in this comment. I am unable to figure out which one I should be using and for the video I see that when the points in either cluster do not overlap it is a valid cluster formation. But in the link example they have created 3 clusters and they are overlapping but still it is considered correct. Could you explain how? I want to find the parameters from my sample sheet being clustered in case of 2,3,4 clusters (which are valid in my case). I wish to find out on the basis of which parameter, R has categorised my samples. Also, the command in the link is not giving me the p-value and kappa as shown in the example. I would highly appreciate any leads on this. I need it urgently for my work. Thank you :))