datarobot.DeploymentRetrainingPolicy
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Deployment Retraining Policy
Example Usage
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package generated_program;
import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.datarobot.DeploymentRetrainingPolicy;
import com.pulumi.datarobot.DeploymentRetrainingPolicyArgs;
import com.pulumi.datarobot.inputs.DeploymentRetrainingPolicyTriggerArgs;
import com.pulumi.datarobot.inputs.DeploymentRetrainingPolicyAutopilotOptionsArgs;
import com.pulumi.datarobot.inputs.DeploymentRetrainingPolicyProjectOptionsArgs;
import com.pulumi.datarobot.inputs.DeploymentRetrainingPolicyTimeSeriesOptionsArgs;
import java.util.List;
import java.util.ArrayList;
import java.util.Map;
import java.io.File;
import java.nio.file.Files;
import java.nio.file.Paths;
public class App {
public static void main(String[] args) {
Pulumi.run(App::stack);
}
public static void stack(Context ctx) {
var example = new DeploymentRetrainingPolicy("example", DeploymentRetrainingPolicyArgs.builder()
.deploymentId(datarobot_deployment.example().id())
.description("Example Description")
.action("create_model_package")
.modelSelectionStrategy("custom_job")
.featureListStrategy("informative_features")
.projectOptionsStrategy("custom")
.trigger(DeploymentRetrainingPolicyTriggerArgs.builder()
.custom_job_id(datarobot_custom_job.example().id())
.build())
.autopilotOptions()
.projectOptions()
.timeSeriesOptions()
.build());
ctx.export("datarobotDeploymentRetrainingPolicyId", example.id());
}
}
resources:
example:
type: datarobot:DeploymentRetrainingPolicy
properties:
deploymentId: ${datarobot_deployment.example.id}
description: Example Description
# Optional
action: create_model_package
modelSelectionStrategy: custom_job
featureListStrategy: informative_features
projectOptionsStrategy: custom
trigger:
custom_job_id: ${datarobot_custom_job.example.id}
autopilotOptions: {}
projectOptions: {}
timeSeriesOptions: {}
outputs:
datarobotDeploymentRetrainingPolicyId: ${example.id}
Create DeploymentRetrainingPolicy Resource
Resources are created with functions called constructors. To learn more about declaring and configuring resources, see Resources.
Constructor syntax
new DeploymentRetrainingPolicy(name: string, args: DeploymentRetrainingPolicyArgs, opts?: CustomResourceOptions);
@overload
def DeploymentRetrainingPolicy(resource_name: str,
args: DeploymentRetrainingPolicyArgs,
opts: Optional[ResourceOptions] = None)
@overload
def DeploymentRetrainingPolicy(resource_name: str,
opts: Optional[ResourceOptions] = None,
deployment_id: Optional[str] = None,
description: Optional[str] = None,
action: Optional[str] = None,
autopilot_options: Optional[DeploymentRetrainingPolicyAutopilotOptionsArgs] = None,
feature_list_strategy: Optional[str] = None,
model_selection_strategy: Optional[str] = None,
name: Optional[str] = None,
project_options: Optional[DeploymentRetrainingPolicyProjectOptionsArgs] = None,
project_options_strategy: Optional[str] = None,
time_series_options: Optional[DeploymentRetrainingPolicyTimeSeriesOptionsArgs] = None,
trigger: Optional[DeploymentRetrainingPolicyTriggerArgs] = None)
func NewDeploymentRetrainingPolicy(ctx *Context, name string, args DeploymentRetrainingPolicyArgs, opts ...ResourceOption) (*DeploymentRetrainingPolicy, error)
public DeploymentRetrainingPolicy(string name, DeploymentRetrainingPolicyArgs args, CustomResourceOptions? opts = null)
public DeploymentRetrainingPolicy(String name, DeploymentRetrainingPolicyArgs args)
public DeploymentRetrainingPolicy(String name, DeploymentRetrainingPolicyArgs args, CustomResourceOptions options)
type: datarobot:DeploymentRetrainingPolicy
properties: # The arguments to resource properties.
options: # Bag of options to control resource's behavior.
Parameters
- name string
- The unique name of the resource.
- args DeploymentRetrainingPolicyArgs
- The arguments to resource properties.
- opts CustomResourceOptions
- Bag of options to control resource's behavior.
- resource_name str
- The unique name of the resource.
- args DeploymentRetrainingPolicyArgs
- The arguments to resource properties.
- opts ResourceOptions
- Bag of options to control resource's behavior.
- ctx Context
- Context object for the current deployment.
- name string
- The unique name of the resource.
- args DeploymentRetrainingPolicyArgs
- The arguments to resource properties.
- opts ResourceOption
- Bag of options to control resource's behavior.
- name string
- The unique name of the resource.
- args DeploymentRetrainingPolicyArgs
- The arguments to resource properties.
- opts CustomResourceOptions
- Bag of options to control resource's behavior.
- name String
- The unique name of the resource.
- args DeploymentRetrainingPolicyArgs
- The arguments to resource properties.
- options CustomResourceOptions
- Bag of options to control resource's behavior.
Constructor example
The following reference example uses placeholder values for all input properties.
var deploymentRetrainingPolicyResource = new Datarobot.DeploymentRetrainingPolicy("deploymentRetrainingPolicyResource", new()
{
DeploymentId = "string",
Description = "string",
Action = "string",
AutopilotOptions = new Datarobot.Inputs.DeploymentRetrainingPolicyAutopilotOptionsArgs
{
BlendBestModels = false,
Mode = "string",
RunLeakageRemovedFeatureList = false,
ScoringCodeOnly = false,
ShapOnlyMode = false,
},
FeatureListStrategy = "string",
ModelSelectionStrategy = "string",
Name = "string",
ProjectOptions = new Datarobot.Inputs.DeploymentRetrainingPolicyProjectOptionsArgs
{
CvMethod = "string",
HoldoutPct = 0,
Metric = "string",
Reps = 0,
ValidationPct = 0,
ValidationType = "string",
},
ProjectOptionsStrategy = "string",
TimeSeriesOptions = new Datarobot.Inputs.DeploymentRetrainingPolicyTimeSeriesOptionsArgs
{
CalendarId = "string",
DifferencingMethod = "string",
ExponentiallyWeightedMovingAlpha = 0,
Periodicities = new[]
{
new Datarobot.Inputs.DeploymentRetrainingPolicyTimeSeriesOptionsPeriodicityArgs
{
TimeSteps = 0,
TimeUnit = "string",
},
},
TreatAsExponential = "string",
},
Trigger = new Datarobot.Inputs.DeploymentRetrainingPolicyTriggerArgs
{
CustomJobId = "string",
MinIntervalBetweenRuns = "string",
Schedule = new Datarobot.Inputs.DeploymentRetrainingPolicyTriggerScheduleArgs
{
DayOfMonths = new[]
{
"string",
},
DayOfWeeks = new[]
{
"string",
},
Hours = new[]
{
"string",
},
Minutes = new[]
{
"string",
},
Months = new[]
{
"string",
},
},
StatusDeclinesToFailing = false,
StatusDeclinesToWarning = false,
StatusStillInDecline = false,
Type = "string",
},
});
example, err := datarobot.NewDeploymentRetrainingPolicy(ctx, "deploymentRetrainingPolicyResource", &datarobot.DeploymentRetrainingPolicyArgs{
DeploymentId: pulumi.String("string"),
Description: pulumi.String("string"),
Action: pulumi.String("string"),
AutopilotOptions: &datarobot.DeploymentRetrainingPolicyAutopilotOptionsArgs{
BlendBestModels: pulumi.Bool(false),
Mode: pulumi.String("string"),
RunLeakageRemovedFeatureList: pulumi.Bool(false),
ScoringCodeOnly: pulumi.Bool(false),
ShapOnlyMode: pulumi.Bool(false),
},
FeatureListStrategy: pulumi.String("string"),
ModelSelectionStrategy: pulumi.String("string"),
Name: pulumi.String("string"),
ProjectOptions: &datarobot.DeploymentRetrainingPolicyProjectOptionsArgs{
CvMethod: pulumi.String("string"),
HoldoutPct: pulumi.Float64(0),
Metric: pulumi.String("string"),
Reps: pulumi.Float64(0),
ValidationPct: pulumi.Float64(0),
ValidationType: pulumi.String("string"),
},
ProjectOptionsStrategy: pulumi.String("string"),
TimeSeriesOptions: &datarobot.DeploymentRetrainingPolicyTimeSeriesOptionsArgs{
CalendarId: pulumi.String("string"),
DifferencingMethod: pulumi.String("string"),
ExponentiallyWeightedMovingAlpha: pulumi.Float64(0),
Periodicities: datarobot.DeploymentRetrainingPolicyTimeSeriesOptionsPeriodicityArray{
&datarobot.DeploymentRetrainingPolicyTimeSeriesOptionsPeriodicityArgs{
TimeSteps: pulumi.Int(0),
TimeUnit: pulumi.String("string"),
},
},
TreatAsExponential: pulumi.String("string"),
},
Trigger: &datarobot.DeploymentRetrainingPolicyTriggerArgs{
CustomJobId: pulumi.String("string"),
MinIntervalBetweenRuns: pulumi.String("string"),
Schedule: &datarobot.DeploymentRetrainingPolicyTriggerScheduleArgs{
DayOfMonths: pulumi.StringArray{
pulumi.String("string"),
},
DayOfWeeks: pulumi.StringArray{
pulumi.String("string"),
},
Hours: pulumi.StringArray{
pulumi.String("string"),
},
Minutes: pulumi.StringArray{
pulumi.String("string"),
},
Months: pulumi.StringArray{
pulumi.String("string"),
},
},
StatusDeclinesToFailing: pulumi.Bool(false),
StatusDeclinesToWarning: pulumi.Bool(false),
StatusStillInDecline: pulumi.Bool(false),
Type: pulumi.String("string"),
},
})
var deploymentRetrainingPolicyResource = new DeploymentRetrainingPolicy("deploymentRetrainingPolicyResource", DeploymentRetrainingPolicyArgs.builder()
.deploymentId("string")
.description("string")
.action("string")
.autopilotOptions(DeploymentRetrainingPolicyAutopilotOptionsArgs.builder()
.blendBestModels(false)
.mode("string")
.runLeakageRemovedFeatureList(false)
.scoringCodeOnly(false)
.shapOnlyMode(false)
.build())
.featureListStrategy("string")
.modelSelectionStrategy("string")
.name("string")
.projectOptions(DeploymentRetrainingPolicyProjectOptionsArgs.builder()
.cvMethod("string")
.holdoutPct(0)
.metric("string")
.reps(0)
.validationPct(0)
.validationType("string")
.build())
.projectOptionsStrategy("string")
.timeSeriesOptions(DeploymentRetrainingPolicyTimeSeriesOptionsArgs.builder()
.calendarId("string")
.differencingMethod("string")
.exponentiallyWeightedMovingAlpha(0)
.periodicities(DeploymentRetrainingPolicyTimeSeriesOptionsPeriodicityArgs.builder()
.timeSteps(0)
.timeUnit("string")
.build())
.treatAsExponential("string")
.build())
.trigger(DeploymentRetrainingPolicyTriggerArgs.builder()
.customJobId("string")
.minIntervalBetweenRuns("string")
.schedule(DeploymentRetrainingPolicyTriggerScheduleArgs.builder()
.dayOfMonths("string")
.dayOfWeeks("string")
.hours("string")
.minutes("string")
.months("string")
.build())
.statusDeclinesToFailing(false)
.statusDeclinesToWarning(false)
.statusStillInDecline(false)
.type("string")
.build())
.build());
deployment_retraining_policy_resource = datarobot.DeploymentRetrainingPolicy("deploymentRetrainingPolicyResource",
deployment_id="string",
description="string",
action="string",
autopilot_options={
"blend_best_models": False,
"mode": "string",
"run_leakage_removed_feature_list": False,
"scoring_code_only": False,
"shap_only_mode": False,
},
feature_list_strategy="string",
model_selection_strategy="string",
name="string",
project_options={
"cv_method": "string",
"holdout_pct": 0,
"metric": "string",
"reps": 0,
"validation_pct": 0,
"validation_type": "string",
},
project_options_strategy="string",
time_series_options={
"calendar_id": "string",
"differencing_method": "string",
"exponentially_weighted_moving_alpha": 0,
"periodicities": [{
"time_steps": 0,
"time_unit": "string",
}],
"treat_as_exponential": "string",
},
trigger={
"custom_job_id": "string",
"min_interval_between_runs": "string",
"schedule": {
"day_of_months": ["string"],
"day_of_weeks": ["string"],
"hours": ["string"],
"minutes": ["string"],
"months": ["string"],
},
"status_declines_to_failing": False,
"status_declines_to_warning": False,
"status_still_in_decline": False,
"type": "string",
})
const deploymentRetrainingPolicyResource = new datarobot.DeploymentRetrainingPolicy("deploymentRetrainingPolicyResource", {
deploymentId: "string",
description: "string",
action: "string",
autopilotOptions: {
blendBestModels: false,
mode: "string",
runLeakageRemovedFeatureList: false,
scoringCodeOnly: false,
shapOnlyMode: false,
},
featureListStrategy: "string",
modelSelectionStrategy: "string",
name: "string",
projectOptions: {
cvMethod: "string",
holdoutPct: 0,
metric: "string",
reps: 0,
validationPct: 0,
validationType: "string",
},
projectOptionsStrategy: "string",
timeSeriesOptions: {
calendarId: "string",
differencingMethod: "string",
exponentiallyWeightedMovingAlpha: 0,
periodicities: [{
timeSteps: 0,
timeUnit: "string",
}],
treatAsExponential: "string",
},
trigger: {
customJobId: "string",
minIntervalBetweenRuns: "string",
schedule: {
dayOfMonths: ["string"],
dayOfWeeks: ["string"],
hours: ["string"],
minutes: ["string"],
months: ["string"],
},
statusDeclinesToFailing: false,
statusDeclinesToWarning: false,
statusStillInDecline: false,
type: "string",
},
});
type: datarobot:DeploymentRetrainingPolicy
properties:
action: string
autopilotOptions:
blendBestModels: false
mode: string
runLeakageRemovedFeatureList: false
scoringCodeOnly: false
shapOnlyMode: false
deploymentId: string
description: string
featureListStrategy: string
modelSelectionStrategy: string
name: string
projectOptions:
cvMethod: string
holdoutPct: 0
metric: string
reps: 0
validationPct: 0
validationType: string
projectOptionsStrategy: string
timeSeriesOptions:
calendarId: string
differencingMethod: string
exponentiallyWeightedMovingAlpha: 0
periodicities:
- timeSteps: 0
timeUnit: string
treatAsExponential: string
trigger:
customJobId: string
minIntervalBetweenRuns: string
schedule:
dayOfMonths:
- string
dayOfWeeks:
- string
hours:
- string
minutes:
- string
months:
- string
statusDeclinesToFailing: false
statusDeclinesToWarning: false
statusStillInDecline: false
type: string
DeploymentRetrainingPolicy Resource Properties
To learn more about resource properties and how to use them, see Inputs and Outputs in the Architecture and Concepts docs.
Inputs
In Python, inputs that are objects can be passed either as argument classes or as dictionary literals.
The DeploymentRetrainingPolicy resource accepts the following input properties:
- Deployment
Id string - The ID of the Deployment for the Retraining Policy.
- Description string
- The description of the Retraining Policy.
- Action string
- The the action to take on the resultant new model.
- Autopilot
Options DataRobot Deployment Retraining Policy Autopilot Options - Options for projects used to build new models.
- Feature
List stringStrategy - The feature list strategy used for modeling.
- Model
Selection stringStrategy - Determines how the new model is selected when the retraining policy runs.
- Name string
- The name of the Retraining Policy.
- Project
Options DataRobot Deployment Retraining Policy Project Options - Options for projects used to build new models.
- Project
Options stringStrategy - The project option strategy used for modeling.
- Time
Series DataOptions Robot Deployment Retraining Policy Time Series Options - Time Series project options used to build new models.
- Trigger
Data
Robot Deployment Retraining Policy Trigger - Retraining policy trigger.
- Deployment
Id string - The ID of the Deployment for the Retraining Policy.
- Description string
- The description of the Retraining Policy.
- Action string
- The the action to take on the resultant new model.
- Autopilot
Options DeploymentRetraining Policy Autopilot Options Args - Options for projects used to build new models.
- Feature
List stringStrategy - The feature list strategy used for modeling.
- Model
Selection stringStrategy - Determines how the new model is selected when the retraining policy runs.
- Name string
- The name of the Retraining Policy.
- Project
Options DeploymentRetraining Policy Project Options Args - Options for projects used to build new models.
- Project
Options stringStrategy - The project option strategy used for modeling.
- Time
Series DeploymentOptions Retraining Policy Time Series Options Args - Time Series project options used to build new models.
- Trigger
Deployment
Retraining Policy Trigger Args - Retraining policy trigger.
- deployment
Id String - The ID of the Deployment for the Retraining Policy.
- description String
- The description of the Retraining Policy.
- action String
- The the action to take on the resultant new model.
- autopilot
Options DeploymentRetraining Policy Autopilot Options - Options for projects used to build new models.
- feature
List StringStrategy - The feature list strategy used for modeling.
- model
Selection StringStrategy - Determines how the new model is selected when the retraining policy runs.
- name String
- The name of the Retraining Policy.
- project
Options DeploymentRetraining Policy Project Options - Options for projects used to build new models.
- project
Options StringStrategy - The project option strategy used for modeling.
- time
Series DeploymentOptions Retraining Policy Time Series Options - Time Series project options used to build new models.
- trigger
Deployment
Retraining Policy Trigger - Retraining policy trigger.
- deployment
Id string - The ID of the Deployment for the Retraining Policy.
- description string
- The description of the Retraining Policy.
- action string
- The the action to take on the resultant new model.
- autopilot
Options DeploymentRetraining Policy Autopilot Options - Options for projects used to build new models.
- feature
List stringStrategy - The feature list strategy used for modeling.
- model
Selection stringStrategy - Determines how the new model is selected when the retraining policy runs.
- name string
- The name of the Retraining Policy.
- project
Options DeploymentRetraining Policy Project Options - Options for projects used to build new models.
- project
Options stringStrategy - The project option strategy used for modeling.
- time
Series DeploymentOptions Retraining Policy Time Series Options - Time Series project options used to build new models.
- trigger
Deployment
Retraining Policy Trigger - Retraining policy trigger.
- deployment_
id str - The ID of the Deployment for the Retraining Policy.
- description str
- The description of the Retraining Policy.
- action str
- The the action to take on the resultant new model.
- autopilot_
options DeploymentRetraining Policy Autopilot Options Args - Options for projects used to build new models.
- feature_
list_ strstrategy - The feature list strategy used for modeling.
- model_
selection_ strstrategy - Determines how the new model is selected when the retraining policy runs.
- name str
- The name of the Retraining Policy.
- project_
options DeploymentRetraining Policy Project Options Args - Options for projects used to build new models.
- project_
options_ strstrategy - The project option strategy used for modeling.
- time_
series_ Deploymentoptions Retraining Policy Time Series Options Args - Time Series project options used to build new models.
- trigger
Deployment
Retraining Policy Trigger Args - Retraining policy trigger.
- deployment
Id String - The ID of the Deployment for the Retraining Policy.
- description String
- The description of the Retraining Policy.
- action String
- The the action to take on the resultant new model.
- autopilot
Options Property Map - Options for projects used to build new models.
- feature
List StringStrategy - The feature list strategy used for modeling.
- model
Selection StringStrategy - Determines how the new model is selected when the retraining policy runs.
- name String
- The name of the Retraining Policy.
- project
Options Property Map - Options for projects used to build new models.
- project
Options StringStrategy - The project option strategy used for modeling.
- time
Series Property MapOptions - Time Series project options used to build new models.
- trigger Property Map
- Retraining policy trigger.
Outputs
All input properties are implicitly available as output properties. Additionally, the DeploymentRetrainingPolicy resource produces the following output properties:
- Id string
- The provider-assigned unique ID for this managed resource.
- Id string
- The provider-assigned unique ID for this managed resource.
- id String
- The provider-assigned unique ID for this managed resource.
- id string
- The provider-assigned unique ID for this managed resource.
- id str
- The provider-assigned unique ID for this managed resource.
- id String
- The provider-assigned unique ID for this managed resource.
Look up Existing DeploymentRetrainingPolicy Resource
Get an existing DeploymentRetrainingPolicy resource’s state with the given name, ID, and optional extra properties used to qualify the lookup.
public static get(name: string, id: Input<ID>, state?: DeploymentRetrainingPolicyState, opts?: CustomResourceOptions): DeploymentRetrainingPolicy
@staticmethod
def get(resource_name: str,
id: str,
opts: Optional[ResourceOptions] = None,
action: Optional[str] = None,
autopilot_options: Optional[DeploymentRetrainingPolicyAutopilotOptionsArgs] = None,
deployment_id: Optional[str] = None,
description: Optional[str] = None,
feature_list_strategy: Optional[str] = None,
model_selection_strategy: Optional[str] = None,
name: Optional[str] = None,
project_options: Optional[DeploymentRetrainingPolicyProjectOptionsArgs] = None,
project_options_strategy: Optional[str] = None,
time_series_options: Optional[DeploymentRetrainingPolicyTimeSeriesOptionsArgs] = None,
trigger: Optional[DeploymentRetrainingPolicyTriggerArgs] = None) -> DeploymentRetrainingPolicy
func GetDeploymentRetrainingPolicy(ctx *Context, name string, id IDInput, state *DeploymentRetrainingPolicyState, opts ...ResourceOption) (*DeploymentRetrainingPolicy, error)
public static DeploymentRetrainingPolicy Get(string name, Input<string> id, DeploymentRetrainingPolicyState? state, CustomResourceOptions? opts = null)
public static DeploymentRetrainingPolicy get(String name, Output<String> id, DeploymentRetrainingPolicyState state, CustomResourceOptions options)
resources: _: type: datarobot:DeploymentRetrainingPolicy get: id: ${id}
- name
- The unique name of the resulting resource.
- id
- The unique provider ID of the resource to lookup.
- state
- Any extra arguments used during the lookup.
- opts
- A bag of options that control this resource's behavior.
- resource_name
- The unique name of the resulting resource.
- id
- The unique provider ID of the resource to lookup.
- name
- The unique name of the resulting resource.
- id
- The unique provider ID of the resource to lookup.
- state
- Any extra arguments used during the lookup.
- opts
- A bag of options that control this resource's behavior.
- name
- The unique name of the resulting resource.
- id
- The unique provider ID of the resource to lookup.
- state
- Any extra arguments used during the lookup.
- opts
- A bag of options that control this resource's behavior.
- name
- The unique name of the resulting resource.
- id
- The unique provider ID of the resource to lookup.
- state
- Any extra arguments used during the lookup.
- opts
- A bag of options that control this resource's behavior.
- Action string
- The the action to take on the resultant new model.
- Autopilot
Options DataRobot Deployment Retraining Policy Autopilot Options - Options for projects used to build new models.
- Deployment
Id string - The ID of the Deployment for the Retraining Policy.
- Description string
- The description of the Retraining Policy.
- Feature
List stringStrategy - The feature list strategy used for modeling.
- Model
Selection stringStrategy - Determines how the new model is selected when the retraining policy runs.
- Name string
- The name of the Retraining Policy.
- Project
Options DataRobot Deployment Retraining Policy Project Options - Options for projects used to build new models.
- Project
Options stringStrategy - The project option strategy used for modeling.
- Time
Series DataOptions Robot Deployment Retraining Policy Time Series Options - Time Series project options used to build new models.
- Trigger
Data
Robot Deployment Retraining Policy Trigger - Retraining policy trigger.
- Action string
- The the action to take on the resultant new model.
- Autopilot
Options DeploymentRetraining Policy Autopilot Options Args - Options for projects used to build new models.
- Deployment
Id string - The ID of the Deployment for the Retraining Policy.
- Description string
- The description of the Retraining Policy.
- Feature
List stringStrategy - The feature list strategy used for modeling.
- Model
Selection stringStrategy - Determines how the new model is selected when the retraining policy runs.
- Name string
- The name of the Retraining Policy.
- Project
Options DeploymentRetraining Policy Project Options Args - Options for projects used to build new models.
- Project
Options stringStrategy - The project option strategy used for modeling.
- Time
Series DeploymentOptions Retraining Policy Time Series Options Args - Time Series project options used to build new models.
- Trigger
Deployment
Retraining Policy Trigger Args - Retraining policy trigger.
- action String
- The the action to take on the resultant new model.
- autopilot
Options DeploymentRetraining Policy Autopilot Options - Options for projects used to build new models.
- deployment
Id String - The ID of the Deployment for the Retraining Policy.
- description String
- The description of the Retraining Policy.
- feature
List StringStrategy - The feature list strategy used for modeling.
- model
Selection StringStrategy - Determines how the new model is selected when the retraining policy runs.
- name String
- The name of the Retraining Policy.
- project
Options DeploymentRetraining Policy Project Options - Options for projects used to build new models.
- project
Options StringStrategy - The project option strategy used for modeling.
- time
Series DeploymentOptions Retraining Policy Time Series Options - Time Series project options used to build new models.
- trigger
Deployment
Retraining Policy Trigger - Retraining policy trigger.
- action string
- The the action to take on the resultant new model.
- autopilot
Options DeploymentRetraining Policy Autopilot Options - Options for projects used to build new models.
- deployment
Id string - The ID of the Deployment for the Retraining Policy.
- description string
- The description of the Retraining Policy.
- feature
List stringStrategy - The feature list strategy used for modeling.
- model
Selection stringStrategy - Determines how the new model is selected when the retraining policy runs.
- name string
- The name of the Retraining Policy.
- project
Options DeploymentRetraining Policy Project Options - Options for projects used to build new models.
- project
Options stringStrategy - The project option strategy used for modeling.
- time
Series DeploymentOptions Retraining Policy Time Series Options - Time Series project options used to build new models.
- trigger
Deployment
Retraining Policy Trigger - Retraining policy trigger.
- action str
- The the action to take on the resultant new model.
- autopilot_
options DeploymentRetraining Policy Autopilot Options Args - Options for projects used to build new models.
- deployment_
id str - The ID of the Deployment for the Retraining Policy.
- description str
- The description of the Retraining Policy.
- feature_
list_ strstrategy - The feature list strategy used for modeling.
- model_
selection_ strstrategy - Determines how the new model is selected when the retraining policy runs.
- name str
- The name of the Retraining Policy.
- project_
options DeploymentRetraining Policy Project Options Args - Options for projects used to build new models.
- project_
options_ strstrategy - The project option strategy used for modeling.
- time_
series_ Deploymentoptions Retraining Policy Time Series Options Args - Time Series project options used to build new models.
- trigger
Deployment
Retraining Policy Trigger Args - Retraining policy trigger.
- action String
- The the action to take on the resultant new model.
- autopilot
Options Property Map - Options for projects used to build new models.
- deployment
Id String - The ID of the Deployment for the Retraining Policy.
- description String
- The description of the Retraining Policy.
- feature
List StringStrategy - The feature list strategy used for modeling.
- model
Selection StringStrategy - Determines how the new model is selected when the retraining policy runs.
- name String
- The name of the Retraining Policy.
- project
Options Property Map - Options for projects used to build new models.
- project
Options StringStrategy - The project option strategy used for modeling.
- time
Series Property MapOptions - Time Series project options used to build new models.
- trigger Property Map
- Retraining policy trigger.
Supporting Types
DeploymentRetrainingPolicyAutopilotOptions, DeploymentRetrainingPolicyAutopilotOptionsArgs
- Blend
Best boolModels - Blend best models during Autopilot run. This option is not supported in SHAP-only mode.
- Mode string
- The autopiltot mode.
- Run
Leakage boolRemoved Feature List - Run Autopilot on Leakage Removed feature list (if exists).
- Scoring
Code boolOnly - Keep only models that can be converted to scorable java code during Autopilot run.
- Shap
Only boolMode - Include only models with SHAP value support.
- Blend
Best boolModels - Blend best models during Autopilot run. This option is not supported in SHAP-only mode.
- Mode string
- The autopiltot mode.
- Run
Leakage boolRemoved Feature List - Run Autopilot on Leakage Removed feature list (if exists).
- Scoring
Code boolOnly - Keep only models that can be converted to scorable java code during Autopilot run.
- Shap
Only boolMode - Include only models with SHAP value support.
- blend
Best BooleanModels - Blend best models during Autopilot run. This option is not supported in SHAP-only mode.
- mode String
- The autopiltot mode.
- run
Leakage BooleanRemoved Feature List - Run Autopilot on Leakage Removed feature list (if exists).
- scoring
Code BooleanOnly - Keep only models that can be converted to scorable java code during Autopilot run.
- shap
Only BooleanMode - Include only models with SHAP value support.
- blend
Best booleanModels - Blend best models during Autopilot run. This option is not supported in SHAP-only mode.
- mode string
- The autopiltot mode.
- run
Leakage booleanRemoved Feature List - Run Autopilot on Leakage Removed feature list (if exists).
- scoring
Code booleanOnly - Keep only models that can be converted to scorable java code during Autopilot run.
- shap
Only booleanMode - Include only models with SHAP value support.
- blend_
best_ boolmodels - Blend best models during Autopilot run. This option is not supported in SHAP-only mode.
- mode str
- The autopiltot mode.
- run_
leakage_ boolremoved_ feature_ list - Run Autopilot on Leakage Removed feature list (if exists).
- scoring_
code_ boolonly - Keep only models that can be converted to scorable java code during Autopilot run.
- shap_
only_ boolmode - Include only models with SHAP value support.
- blend
Best BooleanModels - Blend best models during Autopilot run. This option is not supported in SHAP-only mode.
- mode String
- The autopiltot mode.
- run
Leakage BooleanRemoved Feature List - Run Autopilot on Leakage Removed feature list (if exists).
- scoring
Code BooleanOnly - Keep only models that can be converted to scorable java code during Autopilot run.
- shap
Only BooleanMode - Include only models with SHAP value support.
DeploymentRetrainingPolicyProjectOptions, DeploymentRetrainingPolicyProjectOptionsArgs
- Cv
Method string - The partitioning method for projects used to build new models.
- Holdout
Pct double - The percentage of dataset to assign to holdout set in projects used to build new models.
- Metric string
- The model selection metric in projects used to build new models.
- Reps double
- The number of cross validation folds to use for projects used to build new models.
- Validation
Pct double - The percentage of dataset to assign to validation set in projects used to build new models.
- Validation
Type string - The validation type for projects used to build new models.
- Cv
Method string - The partitioning method for projects used to build new models.
- Holdout
Pct float64 - The percentage of dataset to assign to holdout set in projects used to build new models.
- Metric string
- The model selection metric in projects used to build new models.
- Reps float64
- The number of cross validation folds to use for projects used to build new models.
- Validation
Pct float64 - The percentage of dataset to assign to validation set in projects used to build new models.
- Validation
Type string - The validation type for projects used to build new models.
- cv
Method String - The partitioning method for projects used to build new models.
- holdout
Pct Double - The percentage of dataset to assign to holdout set in projects used to build new models.
- metric String
- The model selection metric in projects used to build new models.
- reps Double
- The number of cross validation folds to use for projects used to build new models.
- validation
Pct Double - The percentage of dataset to assign to validation set in projects used to build new models.
- validation
Type String - The validation type for projects used to build new models.
- cv
Method string - The partitioning method for projects used to build new models.
- holdout
Pct number - The percentage of dataset to assign to holdout set in projects used to build new models.
- metric string
- The model selection metric in projects used to build new models.
- reps number
- The number of cross validation folds to use for projects used to build new models.
- validation
Pct number - The percentage of dataset to assign to validation set in projects used to build new models.
- validation
Type string - The validation type for projects used to build new models.
- cv_
method str - The partitioning method for projects used to build new models.
- holdout_
pct float - The percentage of dataset to assign to holdout set in projects used to build new models.
- metric str
- The model selection metric in projects used to build new models.
- reps float
- The number of cross validation folds to use for projects used to build new models.
- validation_
pct float - The percentage of dataset to assign to validation set in projects used to build new models.
- validation_
type str - The validation type for projects used to build new models.
- cv
Method String - The partitioning method for projects used to build new models.
- holdout
Pct Number - The percentage of dataset to assign to holdout set in projects used to build new models.
- metric String
- The model selection metric in projects used to build new models.
- reps Number
- The number of cross validation folds to use for projects used to build new models.
- validation
Pct Number - The percentage of dataset to assign to validation set in projects used to build new models.
- validation
Type String - The validation type for projects used to build new models.
DeploymentRetrainingPolicyTimeSeriesOptions, DeploymentRetrainingPolicyTimeSeriesOptionsArgs
- Calendar
Id string - The ID of the calendar to be used in this project.
- Differencing
Method string - For time series projects only. Used to specify which differencing method to apply if the data is stationary. For classification problems simple and seasonal are not allowed. Parameter periodicities must be specified if seasonal is chosen. Defaults to auto.
- Exponentially
Weighted doubleMoving Alpha - Discount factor (alpha) used for exponentially weighted moving features.
- Periodicities
List<Data
Robot Deployment Retraining Policy Time Series Options Periodicity> - A list of periodicities for time series projects only. For classification problems periodicities are not allowed. If this is provided, parameter 'differencing*method' will default to 'seasonal' if not provided or 'auto'.
- Treat
As stringExponential - For time series projects only. Used to specify whether to treat data as exponential trend and apply transformations like log-transform. For classification problems always is not allowed. Defaults to auto.
- Calendar
Id string - The ID of the calendar to be used in this project.
- Differencing
Method string - For time series projects only. Used to specify which differencing method to apply if the data is stationary. For classification problems simple and seasonal are not allowed. Parameter periodicities must be specified if seasonal is chosen. Defaults to auto.
- Exponentially
Weighted float64Moving Alpha - Discount factor (alpha) used for exponentially weighted moving features.
- Periodicities
[]Deployment
Retraining Policy Time Series Options Periodicity - A list of periodicities for time series projects only. For classification problems periodicities are not allowed. If this is provided, parameter 'differencing*method' will default to 'seasonal' if not provided or 'auto'.
- Treat
As stringExponential - For time series projects only. Used to specify whether to treat data as exponential trend and apply transformations like log-transform. For classification problems always is not allowed. Defaults to auto.
- calendar
Id String - The ID of the calendar to be used in this project.
- differencing
Method String - For time series projects only. Used to specify which differencing method to apply if the data is stationary. For classification problems simple and seasonal are not allowed. Parameter periodicities must be specified if seasonal is chosen. Defaults to auto.
- exponentially
Weighted DoubleMoving Alpha - Discount factor (alpha) used for exponentially weighted moving features.
- periodicities
List<Deployment
Retraining Policy Time Series Options Periodicity> - A list of periodicities for time series projects only. For classification problems periodicities are not allowed. If this is provided, parameter 'differencing*method' will default to 'seasonal' if not provided or 'auto'.
- treat
As StringExponential - For time series projects only. Used to specify whether to treat data as exponential trend and apply transformations like log-transform. For classification problems always is not allowed. Defaults to auto.
- calendar
Id string - The ID of the calendar to be used in this project.
- differencing
Method string - For time series projects only. Used to specify which differencing method to apply if the data is stationary. For classification problems simple and seasonal are not allowed. Parameter periodicities must be specified if seasonal is chosen. Defaults to auto.
- exponentially
Weighted numberMoving Alpha - Discount factor (alpha) used for exponentially weighted moving features.
- periodicities
Deployment
Retraining Policy Time Series Options Periodicity[] - A list of periodicities for time series projects only. For classification problems periodicities are not allowed. If this is provided, parameter 'differencing*method' will default to 'seasonal' if not provided or 'auto'.
- treat
As stringExponential - For time series projects only. Used to specify whether to treat data as exponential trend and apply transformations like log-transform. For classification problems always is not allowed. Defaults to auto.
- calendar_
id str - The ID of the calendar to be used in this project.
- differencing_
method str - For time series projects only. Used to specify which differencing method to apply if the data is stationary. For classification problems simple and seasonal are not allowed. Parameter periodicities must be specified if seasonal is chosen. Defaults to auto.
- exponentially_
weighted_ floatmoving_ alpha - Discount factor (alpha) used for exponentially weighted moving features.
- periodicities
Sequence[Deployment
Retraining Policy Time Series Options Periodicity] - A list of periodicities for time series projects only. For classification problems periodicities are not allowed. If this is provided, parameter 'differencing*method' will default to 'seasonal' if not provided or 'auto'.
- treat_
as_ strexponential - For time series projects only. Used to specify whether to treat data as exponential trend and apply transformations like log-transform. For classification problems always is not allowed. Defaults to auto.
- calendar
Id String - The ID of the calendar to be used in this project.
- differencing
Method String - For time series projects only. Used to specify which differencing method to apply if the data is stationary. For classification problems simple and seasonal are not allowed. Parameter periodicities must be specified if seasonal is chosen. Defaults to auto.
- exponentially
Weighted NumberMoving Alpha - Discount factor (alpha) used for exponentially weighted moving features.
- periodicities List<Property Map>
- A list of periodicities for time series projects only. For classification problems periodicities are not allowed. If this is provided, parameter 'differencing*method' will default to 'seasonal' if not provided or 'auto'.
- treat
As StringExponential - For time series projects only. Used to specify whether to treat data as exponential trend and apply transformations like log-transform. For classification problems always is not allowed. Defaults to auto.
DeploymentRetrainingPolicyTimeSeriesOptionsPeriodicity, DeploymentRetrainingPolicyTimeSeriesOptionsPeriodicityArgs
- time_
steps int - The number of time steps.
- time_
unit str - The time unit or ROW if windowsBasisUnit is ROW
DeploymentRetrainingPolicyTrigger, DeploymentRetrainingPolicyTriggerArgs
- Custom
Job stringId - Custom job ID for the retraining policy.
- Min
Interval stringBetween Runs - Minimal interval between policy runs in ISO 8601 duration string.
- Schedule
Data
Robot Deployment Retraining Policy Trigger Schedule - Schedule for the retraining policy.
- Status
Declines boolTo Failing - Identifies when trigger type is based on deployment a health status, whether the policy will run when health status declines to failing.
- Status
Declines boolTo Warning - Identifies when trigger type is based on deployment a health status, whether the policy will run when health status declines to warning.
- Status
Still boolIn Decline - Identifies when trigger type is based on deployment a health status, whether the policy will run when health status still in decline.
- Type string
- Type of retraining policy trigger.
- Custom
Job stringId - Custom job ID for the retraining policy.
- Min
Interval stringBetween Runs - Minimal interval between policy runs in ISO 8601 duration string.
- Schedule
Deployment
Retraining Policy Trigger Schedule - Schedule for the retraining policy.
- Status
Declines boolTo Failing - Identifies when trigger type is based on deployment a health status, whether the policy will run when health status declines to failing.
- Status
Declines boolTo Warning - Identifies when trigger type is based on deployment a health status, whether the policy will run when health status declines to warning.
- Status
Still boolIn Decline - Identifies when trigger type is based on deployment a health status, whether the policy will run when health status still in decline.
- Type string
- Type of retraining policy trigger.
- custom
Job StringId - Custom job ID for the retraining policy.
- min
Interval StringBetween Runs - Minimal interval between policy runs in ISO 8601 duration string.
- schedule
Deployment
Retraining Policy Trigger Schedule - Schedule for the retraining policy.
- status
Declines BooleanTo Failing - Identifies when trigger type is based on deployment a health status, whether the policy will run when health status declines to failing.
- status
Declines BooleanTo Warning - Identifies when trigger type is based on deployment a health status, whether the policy will run when health status declines to warning.
- status
Still BooleanIn Decline - Identifies when trigger type is based on deployment a health status, whether the policy will run when health status still in decline.
- type String
- Type of retraining policy trigger.
- custom
Job stringId - Custom job ID for the retraining policy.
- min
Interval stringBetween Runs - Minimal interval between policy runs in ISO 8601 duration string.
- schedule
Deployment
Retraining Policy Trigger Schedule - Schedule for the retraining policy.
- status
Declines booleanTo Failing - Identifies when trigger type is based on deployment a health status, whether the policy will run when health status declines to failing.
- status
Declines booleanTo Warning - Identifies when trigger type is based on deployment a health status, whether the policy will run when health status declines to warning.
- status
Still booleanIn Decline - Identifies when trigger type is based on deployment a health status, whether the policy will run when health status still in decline.
- type string
- Type of retraining policy trigger.
- custom_
job_ strid - Custom job ID for the retraining policy.
- min_
interval_ strbetween_ runs - Minimal interval between policy runs in ISO 8601 duration string.
- schedule
Deployment
Retraining Policy Trigger Schedule - Schedule for the retraining policy.
- status_
declines_ boolto_ failing - Identifies when trigger type is based on deployment a health status, whether the policy will run when health status declines to failing.
- status_
declines_ boolto_ warning - Identifies when trigger type is based on deployment a health status, whether the policy will run when health status declines to warning.
- status_
still_ boolin_ decline - Identifies when trigger type is based on deployment a health status, whether the policy will run when health status still in decline.
- type str
- Type of retraining policy trigger.
- custom
Job StringId - Custom job ID for the retraining policy.
- min
Interval StringBetween Runs - Minimal interval between policy runs in ISO 8601 duration string.
- schedule Property Map
- Schedule for the retraining policy.
- status
Declines BooleanTo Failing - Identifies when trigger type is based on deployment a health status, whether the policy will run when health status declines to failing.
- status
Declines BooleanTo Warning - Identifies when trigger type is based on deployment a health status, whether the policy will run when health status declines to warning.
- status
Still BooleanIn Decline - Identifies when trigger type is based on deployment a health status, whether the policy will run when health status still in decline.
- type String
- Type of retraining policy trigger.
DeploymentRetrainingPolicyTriggerSchedule, DeploymentRetrainingPolicyTriggerScheduleArgs
- Day
Of List<string>Months - Days of the month when the job will run.
- Day
Of List<string>Weeks - Days of the week when the job will run.
- Hours List<string>
- Hours of the day when the job will run.
- Minutes List<string>
- Minutes of the day when the job will run.
- Months List<string>
- Months of the year when the job will run.
- Day
Of []stringMonths - Days of the month when the job will run.
- Day
Of []stringWeeks - Days of the week when the job will run.
- Hours []string
- Hours of the day when the job will run.
- Minutes []string
- Minutes of the day when the job will run.
- Months []string
- Months of the year when the job will run.
- day
Of List<String>Months - Days of the month when the job will run.
- day
Of List<String>Weeks - Days of the week when the job will run.
- hours List<String>
- Hours of the day when the job will run.
- minutes List<String>
- Minutes of the day when the job will run.
- months List<String>
- Months of the year when the job will run.
- day
Of string[]Months - Days of the month when the job will run.
- day
Of string[]Weeks - Days of the week when the job will run.
- hours string[]
- Hours of the day when the job will run.
- minutes string[]
- Minutes of the day when the job will run.
- months string[]
- Months of the year when the job will run.
- day_
of_ Sequence[str]months - Days of the month when the job will run.
- day_
of_ Sequence[str]weeks - Days of the week when the job will run.
- hours Sequence[str]
- Hours of the day when the job will run.
- minutes Sequence[str]
- Minutes of the day when the job will run.
- months Sequence[str]
- Months of the year when the job will run.
- day
Of List<String>Months - Days of the month when the job will run.
- day
Of List<String>Weeks - Days of the week when the job will run.
- hours List<String>
- Hours of the day when the job will run.
- minutes List<String>
- Minutes of the day when the job will run.
- months List<String>
- Months of the year when the job will run.
Package Details
- Repository
- datarobot datarobot-community/pulumi-datarobot
- License
- Apache-2.0
- Notes
- This Pulumi package is based on the
datarobot
Terraform Provider.