Examples_AutoML.md

AutoML

Performing an AutoML style hyperparameter search experiment with Talos could not be any easier.

The single-file code example can be found here.

Imports

import talos
import wrangle

Loading Data

x, y = talos.templates.datasets.cervical_cancer()

# we spare 10% of data for testing later
x, y, x_test, y_test = wrangle.array_split(x, y, .1)

# then validation split
x_train, y_train, x_val, y_val = wrangle.array_split(x, y, .2)

x and y are expected to be either numpy arrays or lists of numpy arrays and same applies for the case where x_train, y_train, x_val, y_val is used instead.

Defining the Model

In this case there is no need to define the model. talos.autom8.AutoModel() is used behind the scenes, where several model architectures fully wired for Talos are found. We simply initiate the AutoScan() object first:

autom8 = talos.autom8.AutoScan('binary', 5)

Parameter Dictionary

There is also no need to worry about the parameter dictionary. This is handled in the background with AutoParams().

Scan()

The Scan() itself is started through the start property of the AutoScan() class object.

autom8.start(x=x_train,
             y=y_train,
             x_val=x_val,
             y_val=y_val,
             fraction_limit=0.000001)

We pass data here just like we would do it in Scan() normally. Also, you are free to use any of the Scan() arguments here to configure the experiment. Find the description for all Scan() arguments here.