Binary Classification
Onboarding a Binary Classification Model
Suppose you would like to onboard a binary classification model for the following dataset.
Following is an example of how you would construct a fdl.ModelInfo
object and onboard such a model.
PROJECT_ID = 'example_project'
DATASET_ID = 'adult_data'
MODEL_ID = 'binary_model'
dataset_info = client.get_dataset_info(
project_id=PROJECT_ID,
dataset_id=DATASET_ID
)
model_task = fdl.ModelTask.BINARY_CLASSIFICATION
model_target = 'income'
model_outputs = ['probability_over_50k']
model_features = [
'age',
'fnlwgt',
'education_num',
'capital_gain',
'capital_loss',
'hours_per_week'
]
model_info = fdl.ModelInfo.from_dataset_info(
dataset_info=dataset_info,
dataset_id=DATASET_ID,
target=model_target,
outputs=model_outputs,
model_task=model_task
)
client.add_model(
project_id=PROJECT_ID,
dataset_id=DATASET_ID,
model_id=MODEL_ID,
model_info=model_info
)
Updated 4 months ago
For information on how to construct a package.py for Binary Classification check the following: