clusterability: clusterability: a package to perform tests of clusterability

In clusterability: Performs Tests for Cluster Tendency of a Data Set

Description

The clusterabilitytest function can test for clusterability of a dataset, and the print function to display output in the console. Below we include code to use with the provided example datasets. Please see the clusterabilitytest function for documentation on available parameters.

Examples

# Normals1
data(normals1)
normals1 <- normals1[,-3]
norm1_dippca <- clusterabilitytest(normals1, "dip")
norm1_dipdist <- clusterabilitytest(normals1, "dip",  distance_standardize = "NONE",
reduction = "distance")
norm1_silvpca <- clusterabilitytest(normals1, "silverman", s_setseed = 123)
norm1_silvdist <- clusterabilitytest(normals1, "silverman", distance_standardize = "NONE",
 reduction = "distance", s_setseed = 123)

print(norm1_dippca)
print(norm1_dipdist)
print(norm1_silvpca)
print(norm1_silvdist)


# Normals2
data(normals2)
normals2 <- normals2[,-3]
norm2_dippca <-
clusterabilitytest(normals2, "dip")
norm2_dipdist <-
clusterabilitytest(normals2, "dip", reduction = "distance", distance_standardize = "NONE")
norm2_silvpca <- clusterabilitytest(normals2, "silverman", s_setseed = 123)
norm2_silvdist <- clusterabilitytest(normals2, "silverman", reduction = "distance",
distance_standardize = "NONE", s_setseed = 123)

print(norm2_dippca)
print(norm2_dipdist)
print(norm2_silvpca)
print(norm2_silvdist)


# Normals3
data(normals3)
normals3 <- normals3[,-3]
norm3_dippca <- clusterabilitytest(normals3, "dip")
norm3_dipdist <- clusterabilitytest(normals3, "dip", reduction = "distance",
distance_standardize = "NONE")
norm3_silvpca <- clusterabilitytest(normals3, "silverman", s_setseed = 123)
norm3_silvdist <- clusterabilitytest(normals3, "silverman", reduction = "distance",
distance_standardize = "NONE", s_setseed = 123)

print(norm3_dippca)
print(norm3_dipdist)
print(norm3_silvpca)
print(norm3_silvdist)



# Normals4
data(normals4)
normals4 <- normals4[,-4]
norm4_dippca <- clusterabilitytest(normals4, "dip")
norm4_dipdist <- clusterabilitytest(normals4, "dip", reduction = "distance",
distance_standardize = "NONE")
norm4_silvpca <- clusterabilitytest(normals4, "silverman", s_setseed = 123)
norm4_silvdist <- clusterabilitytest(normals4, "silverman", reduction = "distance",
distance_standardize = "NONE", s_setseed = 123)

print(norm4_dippca)
print(norm4_dipdist)
print(norm4_silvpca)
print(norm4_silvdist)




# Normals5
data(normals5)
normals5 <- normals5[,-4]
norm5_dippca <- clusterabilitytest(normals5, "dip")
norm5_dipdist <- clusterabilitytest(normals5, "dip", reduction = "distance",
distance_standardize = "NONE")
norm5_silvpca <- clusterabilitytest(normals5, "silverman", s_setseed = 123)
norm5_silvdist <- clusterabilitytest(normals5, "silverman", reduction = "distance",
distance_standardize = "NONE", s_setseed = 123)

print(norm5_dippca)
print(norm5_dipdist)
print(norm5_silvpca)
print(norm5_silvdist)


# iris
data(iris)
newiris <- iris[,c(1:4)]
iris_dippca <- clusterabilitytest(newiris, "dip")
iris_dipdist <- clusterabilitytest(newiris, "dip", reduction = "distance",
distance_standardize = "NONE")
iris_silvpca <- clusterabilitytest(newiris, "silverman", s_setseed = 123)
iris_silvdist <- clusterabilitytest(newiris, "silverman", reduction = "distance",
 distance_standardize = "NONE", s_setseed = 123)

print(iris_dippca)
print(iris_dipdist)
print(iris_silvpca)
print(iris_silvdist)

# cars
data(cars)

cars_dippca <- clusterabilitytest(cars, "dip")
cars_dipdist <- clusterabilitytest(cars, "dip", reduction = "distance",
distance_standardize = "NONE")
cars_silvpca <- clusterabilitytest(cars, "silverman", s_setseed = 123)
cars_silvdist <- clusterabilitytest(cars, "silverman", reduction = "distance",
distance_standardize = "NONE", s_setseed = 123)

print(cars_dippca)
print(cars_dipdist)
print(cars_silvpca)
print(cars_silvdist)

clusterability documentation built on March 13, 2020, 3:07 a.m.