Make Transform from a "FeatureNormalizer" Object

Similar to other transform methods, this function transformed values from a fitted "FeatureNormalizer" object.

# S3 method for FeatureNormalizer
transform(
  model,
  data,
  key,
  features = NULL,
  thread.ratio = NULL,
  division.by.zero.handler = NULL
)

Arguments

model

R6Class object
A "FeatureNormalizer" Object.
data

DataFrame
DataFrame containting the data.
key

character
Name of the ID column.
features

character of list of characters, optional
Name of feature columns for prediction.
If not provided, it defaults to all non-key columns of data.
thread.ratio

double, optional
Controls the proportion of available threads that can be used by this function.
The value range is from 0 to 1, where 0 indicates a single thread, and 1 indicates all available threads.
Values between 0 and 1 will use up to that percentage of available threads.Values outside this range are ignored.
Defaults to 0.
division.by.zero.handler

logical, optional
If TRUE, Throws an error when encountering a division by zero. If FALSE, ignores the column when encountering a division by zero. The column is not scaled.

Value

Dataframe
Transformed variable values corresponding to each data point, structured as follows:

  • ID column, with same name and type as data's ID column.

  • Score columns, type DOUBLE, representing the component score values of each data point.

Examples

Input DataFrame data2 for transform:

> data2$Collect()
     ID S_X1 S_X2
   1  0    6    9
   2  1    6    7
   3  2    4    4
   4  3    1    2
   5  4    9   -2

Perform transform() on the given data2 and "FeatureNormalizer" Object fn:

> result <- transform(fn, data = data2, key = "ID")

Output:

> result$Collect()
    ID        S_X1        S_X2
  1  0  0.00000000  0.03317536
  2  1  0.00000000 -0.06161137
  3  2 -0.06116208 -0.20379147
  4  3 -0.15290520 -0.29857820
  5  4  0.09174312 -0.48815166
  6  5 -0.06116208 -0.15639810

See also

hanaml.FeatureNormalizer