| predict.RandomForestClassifier {hana.ml.r} | R Documentation |
Predict based on model for Random Forest Classifier
Description
Predict based on model for Random Forest Classifier
Usage
## S3 method for class 'RandomForestClassifier'
predict(model, data, key,
features = NULL, verbose = NULL, block.size = NULL,
missing.replacement = NULL)
Arguments
model |
"RandomForestClassifier" object for prediction.
|
data |
DataFrame Independent variable values used for prediction.
|
key |
character Name of the ID column.
|
features |
list of character, optional
Names of the feature columns.
If features is not provided, it defaults to all non-ID columns.
|
verbose |
logical , optional
Defaults to FALSE. Valid only for Classification.
|
block.size |
integer, optional
The number of rows loaded per time during prediction.
0 indicates load all data at once. Defaults to 0.
|
missing.replacement |
character, optional
The missing replacement strategy:
- 'feature_marginalized': marginalise each missing feature out
independently.
- 'instance_marginalized': marginalise all missing features
in an instance as a whole corresponding to each category.
Defaults to feature_marginalized.
|
Value
Dataframe
Predicted values, structured as follows.
ID column, with same name and type as data's ID column.
SCORE, type NVARCHAR, predicted class labels.
CONFIDENCE, type DOUBLE. Representing the confidence of a class
[Package
hana.ml.r version 1.0.8
Index]