Model Predictions — predict • autokeras

Predict the output for a given testing data.

# S3 method for AutokerasModel
predict(object, x, batch_size = 32, ...)

Arguments

object	: A trained AutokerasModel instance.
x	: Any allowed types according to the input node. Testing data. Check corresponding AutokerasModel help to note how it should be provided.
batch_size	: numeric. Defaults to `32`.
...	: Unused.

Value

A one-column matrix with the predicted values as rows.

Examples

if (FALSE) {
library("keras")

# use the MNIST dataset as an example
mnist <- dataset_mnist()
c(x_train, y_train) %<-% mnist$train
c(x_test, y_test) %<-% mnist$test

library("autokeras")

# Initialize the image classifier
clf <- model_image_classifier(max_trials = 10) %>% # It tries 10 different models
  fit(x_train, y_train) # Feed the image classifier with training data

# Predict with the best model
(predicted_y <- clf %>% predict(x_test))

# Evaluate the best model with testing data
clf %>% evaluate(x_test, y_test)

# Get the best trained Keras model, to work with the keras R library
export_model(clf)
}