Computer Science homework help

HW: Nearest Neighbor
1) With the goblet data set, complete the following: Apply other agglomerative methods
to determine appropriate clusters for the standardized and non-standardized data.
Do the results agree with those from the nearest neighbor method examined in
class?
2)Do hierarchical clustering of the tennis racquet data. For clustering, you may pick your
favorite specific approach( . Give the partitions of racquets into clusters, give some
plot(s) to visualize the cluster structure and try to justify #of clusters and characterize
the clusters.
The racquet data can be read in with the following code:
racq.data <- read.table(“racquetsdata.txt”,header=T)
racquet.names <- as.character(racq.data[,1])
racquet.numeric.data <- racq.data[,-1]
The variables in the tennis racquets data set are:
X1 = length of racquet (in inches)
X2 = static weight (in ounces) = this is how much the racquet actually weighs on a scale
X3 = balance (in inches) = this is a measure of whether the racquet is heavier in on the
head end or on the handle end;
more negative values indicate a more head-heavy racquet; positive values indicate a
more head-light racquet;
zero indicates an even balance.
X4 = swingweight = this is a complicated measure of how heavy the racquet FEELS
when it is swung
X5 = headsize (in square inches) = the size of the racquet face (the strung area)
X6 = beamwidth (in mm) = the width of the cross-section (edge) of the racquet