oci.AiAnomalyDetection.getDetectionModels
This data source provides the list of Models in Oracle Cloud Infrastructure Ai Anomaly Detection service.
Returns a list of Models.
Example Usage
using System.Collections.Generic;
using Pulumi;
using Oci = Pulumi.Oci;
return await Deployment.RunAsync(() =>
{
var testModels = Oci.AiAnomalyDetection.GetDetectionModels.Invoke(new()
{
CompartmentId = @var.Compartment_id,
DisplayName = @var.Model_display_name,
ProjectId = oci_ai_anomaly_detection_project.Test_project.Id,
State = @var.Model_state,
});
});
package main
import (
"github.com/pulumi/pulumi-oci/sdk/go/oci/AiAnomalyDetection"
"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)
func main() {
pulumi.Run(func(ctx *pulumi.Context) error {
_, err := AiAnomalyDetection.GetDetectionModels(ctx, &aianomalydetection.GetDetectionModelsArgs{
CompartmentId: _var.Compartment_id,
DisplayName: pulumi.StringRef(_var.Model_display_name),
ProjectId: pulumi.StringRef(oci_ai_anomaly_detection_project.Test_project.Id),
State: pulumi.StringRef(_var.Model_state),
}, nil)
if err != nil {
return err
}
return nil
})
}
package generated_program;
import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.oci.AiAnomalyDetection.AiAnomalyDetectionFunctions;
import com.pulumi.oci.AiAnomalyDetection.inputs.GetDetectionModelsArgs;
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) {
final var testModels = AiAnomalyDetectionFunctions.getDetectionModels(GetDetectionModelsArgs.builder()
.compartmentId(var_.compartment_id())
.displayName(var_.model_display_name())
.projectId(oci_ai_anomaly_detection_project.test_project().id())
.state(var_.model_state())
.build());
}
}
import pulumi
import pulumi_oci as oci
test_models = oci.AiAnomalyDetection.get_detection_models(compartment_id=var["compartment_id"],
display_name=var["model_display_name"],
project_id=oci_ai_anomaly_detection_project["test_project"]["id"],
state=var["model_state"])
import * as pulumi from "@pulumi/pulumi";
import * as oci from "@pulumi/oci";
const testModels = oci.AiAnomalyDetection.getDetectionModels({
compartmentId: _var.compartment_id,
displayName: _var.model_display_name,
projectId: oci_ai_anomaly_detection_project.test_project.id,
state: _var.model_state,
});
variables:
testModels:
fn::invoke:
Function: oci:AiAnomalyDetection:getDetectionModels
Arguments:
compartmentId: ${var.compartment_id}
displayName: ${var.model_display_name}
projectId: ${oci_ai_anomaly_detection_project.test_project.id}
state: ${var.model_state}
Using getDetectionModels
Two invocation forms are available. The direct form accepts plain arguments and either blocks until the result value is available, or returns a Promise-wrapped result. The output form accepts Input-wrapped arguments and returns an Output-wrapped result.
function getDetectionModels(args: GetDetectionModelsArgs, opts?: InvokeOptions): Promise<GetDetectionModelsResult>
function getDetectionModelsOutput(args: GetDetectionModelsOutputArgs, opts?: InvokeOptions): Output<GetDetectionModelsResult>
def get_detection_models(compartment_id: Optional[str] = None,
display_name: Optional[str] = None,
filters: Optional[Sequence[_aianomalydetection.GetDetectionModelsFilter]] = None,
project_id: Optional[str] = None,
state: Optional[str] = None,
opts: Optional[InvokeOptions] = None) -> GetDetectionModelsResult
def get_detection_models_output(compartment_id: Optional[pulumi.Input[str]] = None,
display_name: Optional[pulumi.Input[str]] = None,
filters: Optional[pulumi.Input[Sequence[pulumi.Input[_aianomalydetection.GetDetectionModelsFilterArgs]]]] = None,
project_id: Optional[pulumi.Input[str]] = None,
state: Optional[pulumi.Input[str]] = None,
opts: Optional[InvokeOptions] = None) -> Output[GetDetectionModelsResult]
func GetDetectionModels(ctx *Context, args *GetDetectionModelsArgs, opts ...InvokeOption) (*GetDetectionModelsResult, error)
func GetDetectionModelsOutput(ctx *Context, args *GetDetectionModelsOutputArgs, opts ...InvokeOption) GetDetectionModelsResultOutput
> Note: This function is named GetDetectionModels
in the Go SDK.
public static class GetDetectionModels
{
public static Task<GetDetectionModelsResult> InvokeAsync(GetDetectionModelsArgs args, InvokeOptions? opts = null)
public static Output<GetDetectionModelsResult> Invoke(GetDetectionModelsInvokeArgs args, InvokeOptions? opts = null)
}
public static CompletableFuture<GetDetectionModelsResult> getDetectionModels(GetDetectionModelsArgs args, InvokeOptions options)
// Output-based functions aren't available in Java yet
fn::invoke:
function: oci:AiAnomalyDetection/getDetectionModels:getDetectionModels
arguments:
# arguments dictionary
The following arguments are supported:
- Compartment
Id string The ID of the compartment in which to list resources.
- Display
Name string A filter to return only resources that match the entire display name given.
- Filters
List<Get
Detection Models Filter> - Project
Id string The ID of the project for which to list the objects.
- State string
Filter results by the specified lifecycle state. Must be a valid state for the resource type.
- Compartment
Id string The ID of the compartment in which to list resources.
- Display
Name string A filter to return only resources that match the entire display name given.
- Filters
[]Get
Detection Models Filter - Project
Id string The ID of the project for which to list the objects.
- State string
Filter results by the specified lifecycle state. Must be a valid state for the resource type.
- compartment
Id String The ID of the compartment in which to list resources.
- display
Name String A filter to return only resources that match the entire display name given.
- filters
List<Get
Detection Models Filter> - project
Id String The ID of the project for which to list the objects.
- state String
Filter results by the specified lifecycle state. Must be a valid state for the resource type.
- compartment
Id string The ID of the compartment in which to list resources.
- display
Name string A filter to return only resources that match the entire display name given.
- filters
Get
Detection Models Filter[] - project
Id string The ID of the project for which to list the objects.
- state string
Filter results by the specified lifecycle state. Must be a valid state for the resource type.
- compartment_
id str The ID of the compartment in which to list resources.
- display_
name str A filter to return only resources that match the entire display name given.
- filters
Get
Detection Models Filter] - project_
id str The ID of the project for which to list the objects.
- state str
Filter results by the specified lifecycle state. Must be a valid state for the resource type.
- compartment
Id String The ID of the compartment in which to list resources.
- display
Name String A filter to return only resources that match the entire display name given.
- filters List<Property Map>
- project
Id String The ID of the project for which to list the objects.
- state String
Filter results by the specified lifecycle state. Must be a valid state for the resource type.
getDetectionModels Result
The following output properties are available:
- Compartment
Id string The OCID for the model's compartment.
- Id string
The provider-assigned unique ID for this managed resource.
- Model
Collections List<GetDetection Models Model Collection> The list of model_collection.
- Display
Name string A user-friendly display name for the resource. It does not have to be unique and can be modified. Avoid entering confidential information.
- Filters
List<Get
Detection Models Filter> - Project
Id string The OCID of the project to associate with the model.
- State string
The state of the model.
- Compartment
Id string The OCID for the model's compartment.
- Id string
The provider-assigned unique ID for this managed resource.
- Model
Collections []GetDetection Models Model Collection The list of model_collection.
- Display
Name string A user-friendly display name for the resource. It does not have to be unique and can be modified. Avoid entering confidential information.
- Filters
[]Get
Detection Models Filter - Project
Id string The OCID of the project to associate with the model.
- State string
The state of the model.
- compartment
Id String The OCID for the model's compartment.
- id String
The provider-assigned unique ID for this managed resource.
- model
Collections List<GetDetection Models Model Collection> The list of model_collection.
- display
Name String A user-friendly display name for the resource. It does not have to be unique and can be modified. Avoid entering confidential information.
- filters
List<Get
Detection Models Filter> - project
Id String The OCID of the project to associate with the model.
- state String
The state of the model.
- compartment
Id string The OCID for the model's compartment.
- id string
The provider-assigned unique ID for this managed resource.
- model
Collections GetDetection Models Model Collection[] The list of model_collection.
- display
Name string A user-friendly display name for the resource. It does not have to be unique and can be modified. Avoid entering confidential information.
- filters
Get
Detection Models Filter[] - project
Id string The OCID of the project to associate with the model.
- state string
The state of the model.
- compartment_
id str The OCID for the model's compartment.
- id str
The provider-assigned unique ID for this managed resource.
- model_
collections GetDetection Models Model Collection] The list of model_collection.
- display_
name str A user-friendly display name for the resource. It does not have to be unique and can be modified. Avoid entering confidential information.
- filters
Get
Detection Models Filter] - project_
id str The OCID of the project to associate with the model.
- state str
The state of the model.
- compartment
Id String The OCID for the model's compartment.
- id String
The provider-assigned unique ID for this managed resource.
- model
Collections List<Property Map> The list of model_collection.
- display
Name String A user-friendly display name for the resource. It does not have to be unique and can be modified. Avoid entering confidential information.
- filters List<Property Map>
- project
Id String The OCID of the project to associate with the model.
- state String
The state of the model.
Supporting Types
GetDetectionModelsFilter
GetDetectionModelsModelCollection
GetDetectionModelsModelCollectionItem
- Compartment
Id string The ID of the compartment in which to list resources.
- Dictionary<string, object>
Defined tags for this resource. Each key is predefined and scoped to a namespace. Example:
{"foo-namespace.bar-key": "value"}
- Description string
A short description of the Model.
- Display
Name string A filter to return only resources that match the entire display name given.
- Dictionary<string, object>
Simple key-value pair that is applied without any predefined name, type or scope. Exists for cross-compatibility only. Example:
{"bar-key": "value"}
- Id string
The OCID of the model that is immutable on creation.
- Lifecycle
Details string A message describing the current state in more detail. For example, can be used to provide actionable information for a resource in Failed state.
- Model
Training List<GetDetails Detection Models Model Collection Item Model Training Detail> Specifies the details of the MSET model during the create call.
- Model
Training List<GetResults Detection Models Model Collection Item Model Training Result> Specifies the details for an Anomaly Detection model trained with MSET.
- Project
Id string The ID of the project for which to list the objects.
- State string
Filter results by the specified lifecycle state. Must be a valid state for the resource type.
- Dictionary<string, object>
Usage of system tag keys. These predefined keys are scoped to namespaces. Example:
{"orcl-cloud.free-tier-retained": "true"}
- Time
Created string The time the the Model was created. An RFC3339 formatted datetime string.
- Time
Updated string The time the Model was updated. An RFC3339 formatted datetime string.
- Compartment
Id string The ID of the compartment in which to list resources.
- map[string]interface{}
Defined tags for this resource. Each key is predefined and scoped to a namespace. Example:
{"foo-namespace.bar-key": "value"}
- Description string
A short description of the Model.
- Display
Name string A filter to return only resources that match the entire display name given.
- map[string]interface{}
Simple key-value pair that is applied without any predefined name, type or scope. Exists for cross-compatibility only. Example:
{"bar-key": "value"}
- Id string
The OCID of the model that is immutable on creation.
- Lifecycle
Details string A message describing the current state in more detail. For example, can be used to provide actionable information for a resource in Failed state.
- Model
Training []GetDetails Detection Models Model Collection Item Model Training Detail Specifies the details of the MSET model during the create call.
- Model
Training []GetResults Detection Models Model Collection Item Model Training Result Specifies the details for an Anomaly Detection model trained with MSET.
- Project
Id string The ID of the project for which to list the objects.
- State string
Filter results by the specified lifecycle state. Must be a valid state for the resource type.
- map[string]interface{}
Usage of system tag keys. These predefined keys are scoped to namespaces. Example:
{"orcl-cloud.free-tier-retained": "true"}
- Time
Created string The time the the Model was created. An RFC3339 formatted datetime string.
- Time
Updated string The time the Model was updated. An RFC3339 formatted datetime string.
- compartment
Id String The ID of the compartment in which to list resources.
- Map<String,Object>
Defined tags for this resource. Each key is predefined and scoped to a namespace. Example:
{"foo-namespace.bar-key": "value"}
- description String
A short description of the Model.
- display
Name String A filter to return only resources that match the entire display name given.
- Map<String,Object>
Simple key-value pair that is applied without any predefined name, type or scope. Exists for cross-compatibility only. Example:
{"bar-key": "value"}
- id String
The OCID of the model that is immutable on creation.
- lifecycle
Details String A message describing the current state in more detail. For example, can be used to provide actionable information for a resource in Failed state.
- model
Training List<GetDetails Detection Models Model Collection Item Model Training Detail> Specifies the details of the MSET model during the create call.
- model
Training List<GetResults Detection Models Model Collection Item Model Training Result> Specifies the details for an Anomaly Detection model trained with MSET.
- project
Id String The ID of the project for which to list the objects.
- state String
Filter results by the specified lifecycle state. Must be a valid state for the resource type.
- Map<String,Object>
Usage of system tag keys. These predefined keys are scoped to namespaces. Example:
{"orcl-cloud.free-tier-retained": "true"}
- time
Created String The time the the Model was created. An RFC3339 formatted datetime string.
- time
Updated String The time the Model was updated. An RFC3339 formatted datetime string.
- compartment
Id string The ID of the compartment in which to list resources.
- {[key: string]: any}
Defined tags for this resource. Each key is predefined and scoped to a namespace. Example:
{"foo-namespace.bar-key": "value"}
- description string
A short description of the Model.
- display
Name string A filter to return only resources that match the entire display name given.
- {[key: string]: any}
Simple key-value pair that is applied without any predefined name, type or scope. Exists for cross-compatibility only. Example:
{"bar-key": "value"}
- id string
The OCID of the model that is immutable on creation.
- lifecycle
Details string A message describing the current state in more detail. For example, can be used to provide actionable information for a resource in Failed state.
- model
Training GetDetails Detection Models Model Collection Item Model Training Detail[] Specifies the details of the MSET model during the create call.
- model
Training GetResults Detection Models Model Collection Item Model Training Result[] Specifies the details for an Anomaly Detection model trained with MSET.
- project
Id string The ID of the project for which to list the objects.
- state string
Filter results by the specified lifecycle state. Must be a valid state for the resource type.
- {[key: string]: any}
Usage of system tag keys. These predefined keys are scoped to namespaces. Example:
{"orcl-cloud.free-tier-retained": "true"}
- time
Created string The time the the Model was created. An RFC3339 formatted datetime string.
- time
Updated string The time the Model was updated. An RFC3339 formatted datetime string.
- compartment_
id str The ID of the compartment in which to list resources.
- Mapping[str, Any]
Defined tags for this resource. Each key is predefined and scoped to a namespace. Example:
{"foo-namespace.bar-key": "value"}
- description str
A short description of the Model.
- display_
name str A filter to return only resources that match the entire display name given.
- Mapping[str, Any]
Simple key-value pair that is applied without any predefined name, type or scope. Exists for cross-compatibility only. Example:
{"bar-key": "value"}
- id str
The OCID of the model that is immutable on creation.
- lifecycle_
details str A message describing the current state in more detail. For example, can be used to provide actionable information for a resource in Failed state.
- model_
training_ Getdetails Detection Models Model Collection Item Model Training Detail] Specifies the details of the MSET model during the create call.
- model_
training_ Getresults Detection Models Model Collection Item Model Training Result] Specifies the details for an Anomaly Detection model trained with MSET.
- project_
id str The ID of the project for which to list the objects.
- state str
Filter results by the specified lifecycle state. Must be a valid state for the resource type.
- Mapping[str, Any]
Usage of system tag keys. These predefined keys are scoped to namespaces. Example:
{"orcl-cloud.free-tier-retained": "true"}
- time_
created str The time the the Model was created. An RFC3339 formatted datetime string.
- time_
updated str The time the Model was updated. An RFC3339 formatted datetime string.
- compartment
Id String The ID of the compartment in which to list resources.
- Map<Any>
Defined tags for this resource. Each key is predefined and scoped to a namespace. Example:
{"foo-namespace.bar-key": "value"}
- description String
A short description of the Model.
- display
Name String A filter to return only resources that match the entire display name given.
- Map<Any>
Simple key-value pair that is applied without any predefined name, type or scope. Exists for cross-compatibility only. Example:
{"bar-key": "value"}
- id String
The OCID of the model that is immutable on creation.
- lifecycle
Details String A message describing the current state in more detail. For example, can be used to provide actionable information for a resource in Failed state.
- model
Training List<Property Map>Details Specifies the details of the MSET model during the create call.
- model
Training List<Property Map>Results Specifies the details for an Anomaly Detection model trained with MSET.
- project
Id String The ID of the project for which to list the objects.
- state String
Filter results by the specified lifecycle state. Must be a valid state for the resource type.
- Map<Any>
Usage of system tag keys. These predefined keys are scoped to namespaces. Example:
{"orcl-cloud.free-tier-retained": "true"}
- time
Created String The time the the Model was created. An RFC3339 formatted datetime string.
- time
Updated String The time the Model was updated. An RFC3339 formatted datetime string.
GetDetectionModelsModelCollectionItemModelTrainingDetail
- Algorithm
Hint string User can choose specific algorithm for training.
- Data
Asset List<string>Ids The list of OCIDs of the data assets to train the model. The dataAssets have to be in the same project where the ai model would reside.
- Target
Fap double A target model accuracy metric user provides as their requirement
- Training
Fraction double Fraction of total data that is used for training the model. The remaining is used for validation of the model.
- Window
Size int Window size defined during training or deduced by the algorithm.
- Algorithm
Hint string User can choose specific algorithm for training.
- Data
Asset []stringIds The list of OCIDs of the data assets to train the model. The dataAssets have to be in the same project where the ai model would reside.
- Target
Fap float64 A target model accuracy metric user provides as their requirement
- Training
Fraction float64 Fraction of total data that is used for training the model. The remaining is used for validation of the model.
- Window
Size int Window size defined during training or deduced by the algorithm.
- algorithm
Hint String User can choose specific algorithm for training.
- data
Asset List<String>Ids The list of OCIDs of the data assets to train the model. The dataAssets have to be in the same project where the ai model would reside.
- target
Fap Double A target model accuracy metric user provides as their requirement
- training
Fraction Double Fraction of total data that is used for training the model. The remaining is used for validation of the model.
- window
Size Integer Window size defined during training or deduced by the algorithm.
- algorithm
Hint string User can choose specific algorithm for training.
- data
Asset string[]Ids The list of OCIDs of the data assets to train the model. The dataAssets have to be in the same project where the ai model would reside.
- target
Fap number A target model accuracy metric user provides as their requirement
- training
Fraction number Fraction of total data that is used for training the model. The remaining is used for validation of the model.
- window
Size number Window size defined during training or deduced by the algorithm.
- algorithm_
hint str User can choose specific algorithm for training.
- data_
asset_ Sequence[str]ids The list of OCIDs of the data assets to train the model. The dataAssets have to be in the same project where the ai model would reside.
- target_
fap float A target model accuracy metric user provides as their requirement
- training_
fraction float Fraction of total data that is used for training the model. The remaining is used for validation of the model.
- window_
size int Window size defined during training or deduced by the algorithm.
- algorithm
Hint String User can choose specific algorithm for training.
- data
Asset List<String>Ids The list of OCIDs of the data assets to train the model. The dataAssets have to be in the same project where the ai model would reside.
- target
Fap Number A target model accuracy metric user provides as their requirement
- training
Fraction Number Fraction of total data that is used for training the model. The remaining is used for validation of the model.
- window
Size Number Window size defined during training or deduced by the algorithm.
GetDetectionModelsModelCollectionItemModelTrainingResult
- Fap double
Accuracy metric for a signal.
- Is
Training boolGoal Achieved A boolean value to indicate if train goal/targetFap is achieved for trained model
- Mae double
- Max
Inference intSync Rows - Multivariate
Fap double The model accuracy metric on timestamp level.
- Rmse double
- Row
Reduction List<GetDetails Detection Models Model Collection Item Model Training Result Row Reduction Detail> Information regarding how/what row reduction methods will be applied. If this property is not present or is null, then it means row reduction is not applied.
- Signal
Details List<GetDetection Models Model Collection Item Model Training Result Signal Detail> The list of signal details.
- Warning string
A warning message to explain the reason when targetFap cannot be achieved for trained model
- Window
Size int Window size defined during training or deduced by the algorithm.
- Fap float64
Accuracy metric for a signal.
- Is
Training boolGoal Achieved A boolean value to indicate if train goal/targetFap is achieved for trained model
- Mae float64
- Max
Inference intSync Rows - Multivariate
Fap float64 The model accuracy metric on timestamp level.
- Rmse float64
- Row
Reduction []GetDetails Detection Models Model Collection Item Model Training Result Row Reduction Detail Information regarding how/what row reduction methods will be applied. If this property is not present or is null, then it means row reduction is not applied.
- Signal
Details []GetDetection Models Model Collection Item Model Training Result Signal Detail The list of signal details.
- Warning string
A warning message to explain the reason when targetFap cannot be achieved for trained model
- Window
Size int Window size defined during training or deduced by the algorithm.
- fap Double
Accuracy metric for a signal.
- is
Training BooleanGoal Achieved A boolean value to indicate if train goal/targetFap is achieved for trained model
- mae Double
- max
Inference IntegerSync Rows - multivariate
Fap Double The model accuracy metric on timestamp level.
- rmse Double
- row
Reduction List<GetDetails Detection Models Model Collection Item Model Training Result Row Reduction Detail> Information regarding how/what row reduction methods will be applied. If this property is not present or is null, then it means row reduction is not applied.
- signal
Details List<GetDetection Models Model Collection Item Model Training Result Signal Detail> The list of signal details.
- warning String
A warning message to explain the reason when targetFap cannot be achieved for trained model
- window
Size Integer Window size defined during training or deduced by the algorithm.
- fap number
Accuracy metric for a signal.
- is
Training booleanGoal Achieved A boolean value to indicate if train goal/targetFap is achieved for trained model
- mae number
- max
Inference numberSync Rows - multivariate
Fap number The model accuracy metric on timestamp level.
- rmse number
- row
Reduction GetDetails Detection Models Model Collection Item Model Training Result Row Reduction Detail[] Information regarding how/what row reduction methods will be applied. If this property is not present or is null, then it means row reduction is not applied.
- signal
Details GetDetection Models Model Collection Item Model Training Result Signal Detail[] The list of signal details.
- warning string
A warning message to explain the reason when targetFap cannot be achieved for trained model
- window
Size number Window size defined during training or deduced by the algorithm.
- fap float
Accuracy metric for a signal.
- is_
training_ boolgoal_ achieved A boolean value to indicate if train goal/targetFap is achieved for trained model
- mae float
- max_
inference_ intsync_ rows - multivariate_
fap float The model accuracy metric on timestamp level.
- rmse float
- row_
reduction_ Getdetails Detection Models Model Collection Item Model Training Result Row Reduction Detail] Information regarding how/what row reduction methods will be applied. If this property is not present or is null, then it means row reduction is not applied.
- signal_
details GetDetection Models Model Collection Item Model Training Result Signal Detail] The list of signal details.
- warning str
A warning message to explain the reason when targetFap cannot be achieved for trained model
- window_
size int Window size defined during training or deduced by the algorithm.
- fap Number
Accuracy metric for a signal.
- is
Training BooleanGoal Achieved A boolean value to indicate if train goal/targetFap is achieved for trained model
- mae Number
- max
Inference NumberSync Rows - multivariate
Fap Number The model accuracy metric on timestamp level.
- rmse Number
- row
Reduction List<Property Map>Details Information regarding how/what row reduction methods will be applied. If this property is not present or is null, then it means row reduction is not applied.
- signal
Details List<Property Map> The list of signal details.
- warning String
A warning message to explain the reason when targetFap cannot be achieved for trained model
- window
Size Number Window size defined during training or deduced by the algorithm.
GetDetectionModelsModelCollectionItemModelTrainingResultRowReductionDetail
- Is
Reduction boolEnabled A boolean value to indicate if row reduction is applied
- Reduction
Method string Method for row reduction:
- DELETE_ROW - delete rows with equal intervals
- AVERAGE_ROW - average multiple rows to one row
- Reduction
Percentage double A percentage to reduce data size down to on top of original data
- Is
Reduction boolEnabled A boolean value to indicate if row reduction is applied
- Reduction
Method string Method for row reduction:
- DELETE_ROW - delete rows with equal intervals
- AVERAGE_ROW - average multiple rows to one row
- Reduction
Percentage float64 A percentage to reduce data size down to on top of original data
- is
Reduction BooleanEnabled A boolean value to indicate if row reduction is applied
- reduction
Method String Method for row reduction:
- DELETE_ROW - delete rows with equal intervals
- AVERAGE_ROW - average multiple rows to one row
- reduction
Percentage Double A percentage to reduce data size down to on top of original data
- is
Reduction booleanEnabled A boolean value to indicate if row reduction is applied
- reduction
Method string Method for row reduction:
- DELETE_ROW - delete rows with equal intervals
- AVERAGE_ROW - average multiple rows to one row
- reduction
Percentage number A percentage to reduce data size down to on top of original data
- is_
reduction_ boolenabled A boolean value to indicate if row reduction is applied
- reduction_
method str Method for row reduction:
- DELETE_ROW - delete rows with equal intervals
- AVERAGE_ROW - average multiple rows to one row
- reduction_
percentage float A percentage to reduce data size down to on top of original data
- is
Reduction BooleanEnabled A boolean value to indicate if row reduction is applied
- reduction
Method String Method for row reduction:
- DELETE_ROW - delete rows with equal intervals
- AVERAGE_ROW - average multiple rows to one row
- reduction
Percentage Number A percentage to reduce data size down to on top of original data
GetDetectionModelsModelCollectionItemModelTrainingResultSignalDetail
- Details string
detailed information for a signal.
- Fap double
Accuracy metric for a signal.
- Is
Quantized bool A boolean value to indicate if a signal is quantized or not.
- Max double
Max value within a signal.
- Min double
Min value within a signal.
- Mvi
Ratio double The ratio of missing values in a signal filled/imputed by the IDP algorithm.
- Signal
Name string The name of a signal.
- Status string
Status of the signal:
- ACCEPTED - the signal is used for training the model
- DROPPED - the signal does not meet requirement, and is dropped before training the model.
- OTHER - placeholder for other status
- Std double
Standard deviation of values within a signal.
- Details string
detailed information for a signal.
- Fap float64
Accuracy metric for a signal.
- Is
Quantized bool A boolean value to indicate if a signal is quantized or not.
- Max float64
Max value within a signal.
- Min float64
Min value within a signal.
- Mvi
Ratio float64 The ratio of missing values in a signal filled/imputed by the IDP algorithm.
- Signal
Name string The name of a signal.
- Status string
Status of the signal:
- ACCEPTED - the signal is used for training the model
- DROPPED - the signal does not meet requirement, and is dropped before training the model.
- OTHER - placeholder for other status
- Std float64
Standard deviation of values within a signal.
- details String
detailed information for a signal.
- fap Double
Accuracy metric for a signal.
- is
Quantized Boolean A boolean value to indicate if a signal is quantized or not.
- max Double
Max value within a signal.
- min Double
Min value within a signal.
- mvi
Ratio Double The ratio of missing values in a signal filled/imputed by the IDP algorithm.
- signal
Name String The name of a signal.
- status String
Status of the signal:
- ACCEPTED - the signal is used for training the model
- DROPPED - the signal does not meet requirement, and is dropped before training the model.
- OTHER - placeholder for other status
- std Double
Standard deviation of values within a signal.
- details string
detailed information for a signal.
- fap number
Accuracy metric for a signal.
- is
Quantized boolean A boolean value to indicate if a signal is quantized or not.
- max number
Max value within a signal.
- min number
Min value within a signal.
- mvi
Ratio number The ratio of missing values in a signal filled/imputed by the IDP algorithm.
- signal
Name string The name of a signal.
- status string
Status of the signal:
- ACCEPTED - the signal is used for training the model
- DROPPED - the signal does not meet requirement, and is dropped before training the model.
- OTHER - placeholder for other status
- std number
Standard deviation of values within a signal.
- details str
detailed information for a signal.
- fap float
Accuracy metric for a signal.
- is_
quantized bool A boolean value to indicate if a signal is quantized or not.
- max float
Max value within a signal.
- min float
Min value within a signal.
- mvi_
ratio float The ratio of missing values in a signal filled/imputed by the IDP algorithm.
- signal_
name str The name of a signal.
- status str
Status of the signal:
- ACCEPTED - the signal is used for training the model
- DROPPED - the signal does not meet requirement, and is dropped before training the model.
- OTHER - placeholder for other status
- std float
Standard deviation of values within a signal.
- details String
detailed information for a signal.
- fap Number
Accuracy metric for a signal.
- is
Quantized Boolean A boolean value to indicate if a signal is quantized or not.
- max Number
Max value within a signal.
- min Number
Min value within a signal.
- mvi
Ratio Number The ratio of missing values in a signal filled/imputed by the IDP algorithm.
- signal
Name String The name of a signal.
- status String
Status of the signal:
- ACCEPTED - the signal is used for training the model
- DROPPED - the signal does not meet requirement, and is dropped before training the model.
- OTHER - placeholder for other status
- std Number
Standard deviation of values within a signal.
Package Details
- Repository
- oci pulumi/pulumi-oci
- License
- Apache-2.0
- Notes
This Pulumi package is based on the
oci
Terraform Provider.