Hi everyone, for my undergraduate research project, I'm looking for an R code for agglomerative clustering. Basically, I need to know what happened inside hclust method in R. I have looked everywhere but don't find a proper way to combine 2 data points that have the smallest distance. I was stuck at developing a dissimilarity matrix after the first phase of dissimilarity matrix generation(literally I have generated the first dissimilarity matrix). I'm not specifying R, if anyone could give me a solution in any language I would gratefully accept that.

The thickness of a part is to have an upper specification of 0.925 and a lower specification of 0.870 mm. the average of the process is currently 0.917 with a standard deviation of 0.005. determine the percentage of product above 0.93 mm.

Ou listened to a song on your computer. did you use hardware or software?

What is the worst-case complexity of the maxrepeats function? assume that the longest string in the names array is at most 25 characters wide (i.e., string comparison can be treated as o( class namecounter { private: int* counts; int nc; string* names; int nn; public: namecounter (int ncounts, int nnames); int maxrepeats() const; }; int namecounter: : maxrepeats () { int maxcount = 0; for (int i = 0; i < nc; ++i) { int count = 1; for (int j = i+1; j < nc; ++j) { if (names[i] == names[j]) ++count; } maxcount = max(count, maxcount); } return maxcount; }