--- predict ---

Model inference. Returns HEMatrix that contains logits, and has shape of (batch_size, num_classes)

predict(model, mat)

Arguments

mat:

(HEMatrix) - Input matrix of shape (num_data, num_features).

Value

HEMatrix: Output HEMatrix, Dot-product of the input matrix and the model parameter.

Examples

if (FALSE) {
params <- heaan_sdk.HEParameter("FGb")
context <- heaan_sdk.Context(
     params,
     key_dir_path = key_dir_path,
     load_keys = "all",
     generate_keys = TRUE)
library(caret)
data(iris)
set.seed(34)
trainIndex <- createDataPartition(iris$Species,
             times = 1, p = 0.8, list = FALSE)
X_train <- iris[trainIndex, 1:4]
X_test <- iris[-trainIndex, 1:4]
y_train <- as.integer(iris[trainIndex, 5]) - 1
y_test <- as.integer(iris[-trainIndex, 5])- 1
classes <- c(0, 1, 2)
num_feature <- ncol(X_train)
batch_size <- 128
unit_shape <- (as.integer(c(batch_size,
             floor(py_to_r(context$num_slots) / batch_size))))
test_data_feature <- encode_encrypt(context,
                                     X_test,
                                     unit_shape,
                                     target_level = 3)
}