predict.LogisticRegression.Rd
Similar to other predict methods, this function predicts fitted values from a fitted "LogisticRegression" object.
# S3 method for LogisticRegression
predict(
model,
key,
data,
features = NULL,
verbose = FALSE,
thread.ratio = NULL,
multi.class = NULL,
class.map0 = NULL,
class.map1 = NULL,
categorical.variable = NULL
)
S3
methods
R6Class object
A "LogisticRegression" object for prediction.
character
Name of the ID column.
DataFrame
DataFrame containting the data.
character of list of characters, optional
Name of feature columns for prediction.
If not provided, it defaults to all non-key columns of data.
logical, optional
If TRUE, output all classes and the corresponding
confidences for each data point.
Defaults to FALSE.
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.
logical, optional
If the value is TRUE, prediction for multi-class classification is performed.
Otherwise prediction for binary classification is performed.
Defaults to model$multi.class
.
character, optional
Categorical label to map to 0.
Only valid when multi.class
or model$multi.class
is FALSE.
class.map0
is mandatory when label column type is VARCHAR or
NVARCHAR during binary class fit and score.
Defaults to model$class.map0
.
character, optional
Categorical label to map to 1.
Only valid when multi.class
or model$multi.class
is FALSE.
class.map1
is mandatory when label column type is VARCHAR or
NVARCHAR during binary class fit and score.
Defaults to model$class.map1
.
character or list/vector of characters, optional
Indicates features should be treated as categorical variable.
The default behavior is dependent on what input is given:
"VARCHAR" and "NVARCHAR": categorical
"INTEGER" and "DOUBLE": continuous.
VALID only for variables of "INTEGER" type, omitted otherwise.
No default value.
Returns a Dataframe
containing predicted values, structured as follows.
ID column, with same name and type as data
's ID column.
CLASS, type NVARCHAR, predicted class name.
PROBABILITY, type DOUBLE.
lr is a "LogisticRegression" object.
Call the function:
> predict(model=lr, data=data.predict, key="ID", features=list("V1", "V2", "V3"))