predict.FFMClassifier.Rd
Make Predictions from an "FFMClassifier" Object
# S3 method for FFMClassifier
predict(
model = NULL,
data = NULL,
key = NULL,
features = NULL,
handle.missing = NULL,
thread.ratio = NULL
)
S3
methods
R6Class object
A "FFMClassifier" object for prediction.
DataFrame
DataFrame containting data of user-item interaction and global
side features for prediction.
character
Name of the ID column.
list of characters, optional
Name of feature columns.
If not provided, it defaults all non-ID columns of
data.
c("remove", "replace"), optional
Specifies how to handle missing features of data
:
"remove"
remove missing rows
"replace"
replace missing rows with 0
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.
DataFrame
Prediction made by the model, structured as follows:
ID: id.
SCORE: Predict value.
CONFIDENCE: the confidence of a category (NULL for "regression").
> data$Collect()
ID USER MOVIE TIMESTAMP
1 1 A Movie0 3
2 2 A Movie4 1
3 3 B Movie3 2
4 4 B <NA> 5
5 5 C Movie2 2
6 6 F Movie4 3
7 7 D Movie2 2
8 8 D Movie4 1
9 9 E Movie7 4
Call the function:
> cres <- predict.FFMClassifier(model = FFMClsf,
data = data.pred.df.fit,
thread.ratio = 1)
Output:
> cres$Head(5)
ID SCORE CONFIDENCE
1 1 Not click 0.5435375
2 2 Not click 0.5454705
3 3 Click 0.5427368
4 4 Click 0.5194578
5 5 Click 0.5110010