predict.ALS.Rd
Similar to other predict methods, this function predicts fitted values from a fitted "ALS" object.
# S3 method for ALS
predict(model, data, key, used.cols = NULL, thread.ratio = NULL, ...)
S3
methods
R6Class object
An "ALS" object for prediction.
DataFrame
DataFrame containting the data.
character
Name of the ID column.
list/vector of character, optional
Specifies the three columns of data that are used for model prediction.
Should arranged in the order of: user, item.
Otherwise, the list/vector must be named, shown as follows:
used.cols <- list(user = xxx, item = xxx)
Default to the first two non-ID columns if not provided..
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.
Reserved parameter.
Predicted values are returned as a DataFrame, structured as follows.
ID column, with same name and type as `data`'s ID column.
user column, representing user names/IDs.
item column, represnetiing item names/IDs.
PREDICTION column, predicted feedback of user to item.
Perform the predict on DataFrame data2 using "ALS" object als:
> data2$Collect()
ID USER MOVIE
1 1 A Movie3
2 2 A Movie7
3 3 B Movie1
4 4 B Movie6
5 5 C Movie3
6 6 D Movie2
7 7 D Movie5
8 8 E Bad_Movie
Call the function and obtain the result:
> pred.res <- predict(als, data = data2,
key = "ID",
used.cols = c(user = "USER"))
> pred.res$Collect()
ID USER MOVIE PREDICTION
1 1 A Movie3 3.868747
2 2 A Movie7 2.870243
3 3 B Movie1 5.787559
4 4 B Movie6 5.837218
5 5 C Movie3 3.323575
6 6 D Movie2 4.156372
7 7 D Movie5 4.325851
8 8 E Bad_Movie 2.545807