Keras extension for openml-python API.
pip install openml-keras
PyPi link https://pypi.org/project/openml-keras/
Import openML libraries
import openml
import openml_keras
Create and compile a keras model
model = keras.models.Sequential([
keras.layers.BatchNormalization(),
keras.layers.Dense(units=1024, activation=keras.activations.relu),
keras.layers.Dropout(rate=0.4),
keras.layers.Dense(units=2, activation=keras.activations.softmax),
])
# We will compile using the Adam optimizer while targeting accuracy.
model.compile(optimizer='adam',
loss='sparse_categorical_crossentropy',
metrics=['accuracy'])
Download the task from openML and run the model on task.
task = openml.tasks.get_task(3573)
run = openml.runs.run_model_on_task(model, task, avoid_duplicate_runs=False)
run.publish()
print('URL for run: %s/run/%d' % (openml.config.server, run.run_id))
Note: The input layer of the network should be compatible with OpenML data output shape. Please check examples for more information.