| listBuiltInFunctions {clusterExperiment} | R Documentation |
Documents the built-in clustering options that are available in the clusterExperiment package.
listBuiltInFunctions() ## S4 method for signature 'character' getBuiltInFunction(object) listBuiltInTypeK() listBuiltInType01()
object |
name of built in function. |
listBuiltInFunctions will return the character names of
the built-in clustering functions available.
listBuiltInTypeK returns the names of the built-in functions
that have type 'K'
listBuiltInType01 returns the names of the built-in functions
that have type '01'
getBuiltInFunction will return the
ClusterFunction object of a character value that corresponds to a
built-in function.
algorithmType and inputType will
return the algorithmType and inputType of the
built-in clusterFunction corresponding to the character value.
Built-in clustering methods: The built-in clustering methods, the
names of which can be accessed by listBuiltInFunctions() are the
following:
"pam"Based on pam in
cluster package. Arguments to that function can be passed via
clusterArgs.
Input is "either" (x or diss); algorithm type is "K"
"clara"Based on clara in
cluster package. Arguments to that function can be passed via
clusterArgs. Note that we have changed the default arguments of
that function to match the recommendations in the documentation of
clara (numerous functions are set to less than optimal
settings for back-compatiability). Specifically, the following defaults
are implemented samples=50, keep.data=FALSE,
mediods.x=FALSE,rngR=TRUE,
pamLike=TRUE, correct.d=TRUE.
Input is "X"; algorithm type is "K".
"kmeans"Based on kmeans in
stats package. Arguments to that function can be passed via
clusterArgs except for centers which is reencoded here to be
the argument 'k'
Input is "X"; algorithm type is "K"
"hierarchical01"hclust in
stats package is used to build hiearchical clustering. Arguments to
that function can be passed via clusterArgs. The
hierarchical01 cuts the hiearchical tree based on the parameter
alpha. It does not use the cutree function, but instead
transversing down the tree until getting a block of
samples with whose summary of the values is greater than or equal to
1-alpha. Arguments that can be passed to 'hierarchical01' are
'evalClusterMethod' which determines how to summarize the samples' values
of D[samples,samples] for comparison to 1-alpha: "maximum" (default) takes
the minimum of D[samples,samples] and requires it to be less than or equal
to 1-alpha; "average" requires that each row mean of D[samples,samples] be
less than or equal to 1-alpha. Additional arguments of hclust can also be passed via
clusterArgs to control the hierarchical clustering of D.
Input is "diss"; algorithm type is "01"
"hierarchicalK"hclust in stats package is used
to build hiearchical clustering and cutree is used to cut the
tree into k clusters.
Input is "diss"; algorithm type is "K"
"tight"Based on the algorithm in
Tsang and Wong, specifically their method of picking clusters from a
co-occurance matrix after subsampling. The clustering encoded here is not
the entire tight clustering algorithm, only that single piece that
identifies clusters from the co-occurance matrix.
Arguments for the tight method are
'minSize.core' (default=2), which sets the minimimum number of samples that
form a core cluster.
Input is "diss"; algorithm type is "01"
"spectral"specc in kernlab package
is used to perform spectral clustering. Note that spectral clustering can
produce errors if the number of clusters (K) is not sufficiently smaller than
the number of samples (N). K < N is not always sufficient.
Input is "X"; algorithm type is "K".
listBuiltInFunctions returns a character vector of all
the built-in cluster functions' names.
getBuiltInFunction returns the ClusterFunction
object that corresponds to the character name of a function
listBuiltInTypeK returns a character vector of the
names of built-in cluster functions that are of type "K"
listBuiltInType01 returns a character vector of the
names of built-in cluster functions that are of type "01"
ClusterFunction, algorithmType,
inputType
listBuiltInFunctions()
algorithmType(c("kmeans","pam","hierarchical01"))
inputType(c("kmeans","pam","hierarchical01"))
listBuiltInTypeK()
listBuiltInType01()