transform.Discretize.Rd
Similar to other transform methods, this function transforms values from a fitted "Kmeans" object.
# S3 method for Discretize
transform(model, data, key, features = NULL)
R6Class object
A "Discretize" Object.
DataFrame
DataFrame containting the data.
character
Name of the ID column.
character of list of characters, optional
Name of feature columns.
If not provided, it defaults all non-key, non-label columns of data.
Transformed values are returned as a DataFrame, structured as follows.
ID column, with same name and type as data 's ID column.
Cluster_ID, type INTEGER, the assigned cluster ID.
DISTANCE, type DOUBLE, Distance between a given point and the cluster center.
Perform the transformation on DataFrame data2 using "Discretize" object discretize:
> discretize.df.apply$Collect()
ID ATT1 ATT2 ATT3 ATT4
1 1 20.0 120 1 A
2 2 30.0 101 1 A
3 3 10.7 143 1 B
4 4 15.8 256 1 C
5 5 88.9 100 1 A
6 6 76.5 402 4 A
7 7 55.3 905 4 B
Call the function:
> result <- transform(discretize, discretize.df.apply, key = "ID",
features = list("ATT1", "ATT2", "ATT3", "ATT4"))
Output:
> result[[1]]$Collect()
ID ATT1 ATT2 ATT3 ATT4
1 1 10.2 100.8 1 A
2 2 10.2 100.8 1 A
3 3 10.2 100.8 1 B
4 4 10.2 100.8 1 C
5 5 90.2 900.8 1 A
6 6 90.2 900.8 4 A
7 7 40.2 400.8 4 B