Description Usage Arguments Details Value Constraints See Also Examples
FLVarCluster
performs variable clustering on FLTable objects
using Principal Component Analysis
1 | FLVarCluster(x, ...)
|
x |
an object of class FLTable, wide or deep |
contrib |
Level of contribution expected in the output clusters. Value between 0 and 1 |
matrixType |
whether a correlation matrix or a covariance matrix should be used for Eigenvalue decomposition. Allowed values c("COVAR","CORREL") |
groupBy |
Comma separated column names identifying each data set. Currently not used and NULL always. |
excludeCols |
the comma separated character string of columns to be excluded |
classSpec |
list describing the categorical dummy variables |
whereconditions |
takes the where_clause as a string |
The DB Lytix function called is FLVarCluster. Uses a principal component analysis for dimensionality reduction in order to cluster a given set of input variables into a smaller representative set. The number of output clusters depend on the contribution level specified.
FLVarCluster
returns a R vector if data can be fetched
or a FLVector of cluster to which each variable or column is assigned.
If classSpec is not specified, the categorical variables are excluded from analysis by default.
ClustOfVar
package for R reference implementation.
1 2 3 4 | deeptable <- FLTable(getTestTableName("tblLogRegr"), "ObsID","VarID",
"Num_Val", whereconditions= "ObsID<101")
clustervector <- FLVarCluster(deeptable,0.75,"COVAR",whereconditions=" VarID>0 ")
print(clustervector)
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