ml training create
Create a Watson Machine Learning training.
Syntax
cpd-cli ml training create \
[--async] \
[--context=<catalog-project-or-space-id>] \
[--cpd-config=<cpd-config-location>] \
[--cpd-scope=<cpd-config-location>] \
[--custom=<map<key,value>>] \
[--description=<training-description>] \
[--experiment=<resource-reference>] \
[--federated-learning=<technical-preview>] \
[--jmes-query=<jmespath-query>] \
[--name=<training-name>] \
[--output=json|yaml|table] \
[--output-file=<output-file-location>] \
[--pipeline=<resource-reference>] \
--profile=<cpd-configuration-profile-name> \
[--project-id=<cpd-project-id>] \
[--quiet] \
[--raw-output=true|false] \
--results-reference=<training-results> \
[--space-id=<space-identifier>] \
[--tags=<tag1,tag2,...>] \
[--test-data-references=<holdout-or-test-data-set>] \
[--training-data-references=<model-training-data>]\
[--verbose]
Arguments
The ml training create
command has
no arguments.
Options
Option | Description |
---|---|
--async |
Run the command asynchronously. By default, processing finishes before the command runs.
|
--context |
Specify the configuration context
name.
|
--cpd-config |
The Cloud Pak for Data
configuration location (for example, $HOME/.cpd-cli/config).
|
--cpd-scope |
The Cloud Pak for Data space, project, or catalog scope (for example, cpd://default-context/spaces/7bccdda4-9752-4f37-868e-891de6c48135).
|
--custom |
Specify user-defined properties as key-value pairs.
|
--description |
Specify a training
description.
|
--experiment |
Specify a reference to a resource.
|
--federated-learning |
Specify the Federated Learning. The Federated Learning is a technical preview.
|
|
Display command
help.
|
--jmes-query |
Provide a JMESPath query to customize the output.
|
--model-definition |
Specify the model definition. The 'software_spec' is a reference to a software specification. The 'hardware_spec' is a reference to a hardware specification.
|
--name |
Specify a training name.
|
--output |
Specify an output format.
Valid formats include json, yaml, or text (the default
format).
|
--output-file |
Specify a file path where all output is redirected.
|
--pipeline |
Specify a reference to a resource. The 'hardware_spec' is a reference to the hardware specification. The 'hybrid_pipeline_hardware_specs' reference is used only when training a hybrid pipeline. A hybrid pipeline is used to specify the compute requirements for each pipeline node.
|
--profile |
The profile-name from the Cloud
Pak for Data configuration.
|
--project-id |
Specify a Cloud Pak for Data project instance that contains the resource.
|
--quiet |
Suppress verbose messages.
|
--raw-output |
When set to true, single values in
JSON output mode are not surrounded by quotes.
|
--results-reference |
Specify the training results.
|
--space-id |
Specify a space identifier.
|
--tags |
Specify tags that can be used when searching for resources.
|
--test-data-references |
Specify the holdout or test data sets.
|
--training-data-references |
Specify the training data that was used to create the model.
|
--verbose |
Logs include more detailed
messages.
|