export interface DatasetSchema {
    /** The data schema used within the given dataset. */
    InlineDataSchema?: string;
}
export interface Tag {
    /** The key for the specified tag. */
    Key: string;
    /** The value for the specified tag. */
    Value: string;
}
export interface InferenceS3InputConfiguration {
    /** The bucket containing the input dataset for the inference. */
    Bucket: string;
    /** The prefix for the S3 bucket used for the input data for the inference. */
    Prefix?: string;
}
export interface InferenceInputNameConfiguration {
    /** The format of the timestamp, whether Epoch time, or standard, with or without hyphens (-). */
    TimestampFormat?: string;
    /** Indicates the delimiter character used between items in the data. */
    ComponentTimestampDelimiter?: string;
}
export interface InferenceInputConfiguration {
    /** Specifies configuration information for the input data for the inference, including Amazon S3 location of input data. */
    S3InputConfiguration?: InferenceS3InputConfiguration;
    /** Indicates the difference between your time zone and Coordinated Universal Time (UTC). */
    InputTimeZoneOffset?: string;
    /** Specifies configuration information for the input data for the inference, including timestamp format and delimiter. */
    InferenceInputNameConfiguration?: InferenceInputNameConfiguration;
}
export interface InferenceS3OutputConfiguration {
    /** The bucket containing the output results from the inference */
    Bucket: string;
    /** The prefix for the S3 bucket used for the output results from the inference. */
    Prefix?: string;
}
export interface InferenceOutputConfiguration {
    /** Specifies configuration information for the output results from for the inference, output S3 location. */
    S3OutputConfiguration: InferenceS3OutputConfiguration;
    /** The ID number for the KMS key key used to encrypt the inference output. */
    KmsKeyId?: string;
}
export interface LabelsS3InputConfiguration {
    /** The name of the S3 bucket holding the label data. */
    Bucket: string;
    /** The prefix for the S3 bucket used for the label data. */
    Prefix?: string;
}
export interface LabelsInputConfiguration {
    /** Contains location information for the S3 location being used for label data. */
    S3InputConfiguration?: LabelsS3InputConfiguration;
    /** The name of the label group to be used for label data. */
    LabelGroupName?: string;
}
export interface DataPreProcessingConfiguration {
    /** The sampling rate of the data after post processing by Amazon Lookout for Equipment. For example, if you provide data that has been collected at a 1 second level and you want the system to resample th */
    TargetSamplingRate?: 'PT1S' | 'PT5S' | 'PT10S' | 'PT15S' | 'PT30S' | 'PT1M' | 'PT5M' | 'PT10M' | 'PT15M' | 'PT30M' | 'PT1H';
}
export interface ModelDiagnosticsS3OutputConfiguration {
    /** The name of the Amazon S3 bucket where the pointwise model diagnostics are located. You must be the owner of the Amazon S3 bucket. */
    Bucket: string;
    /** The Amazon S3 prefix for the location of the pointwise model diagnostics. The prefix specifies the folder and evaluation result file name. (bucket). When you call CreateModel or UpdateModel, specify t */
    Prefix?: string;
}
export interface ModelDiagnosticsOutputConfiguration {
    /** The Amazon S3 location for the pointwise model diagnostics. */
    S3OutputConfiguration: ModelDiagnosticsS3OutputConfiguration;
    /** The Amazon Web Services Key Management Service (KMS) key identifier to encrypt the pointwise model diagnostics files. */
    KmsKeyId?: string;
}
export interface IngestionS3InputConfiguration {
    /** The name of the S3 bucket used for the input data for the data ingestion. */
    Bucket: string;
    /** The prefix for the S3 location being used for the input data for the data ingestion. */
    Prefix?: string;
    /** The pattern for matching the Amazon S3 files that will be used for ingestion. If the schema was created previously without any KeyPattern, then the default KeyPattern {prefix}/{component_name}/* is us */
    KeyPattern?: string;
}
export interface IngestionInputConfiguration {
    /** The location information for the S3 bucket used for input data for the data ingestion. */
    S3InputConfiguration: IngestionS3InputConfiguration;
}
export interface CreateDatasetInput {
    /** A unique identifier for the request. If you do not set the client request token, Amazon Lookout for Equipment generates one. */
    ClientToken: string;
    /** The name of the dataset being created. */
    DatasetName: string;
    /** A JSON description of the data that is in each time series dataset, including names, column names, and data types. */
    DatasetSchema?: DatasetSchema;
    /** Provides the identifier of the KMS key used to encrypt dataset data by Amazon Lookout for Equipment. */
    ServerSideKmsKeyId?: string;
    /** Any tags associated with the ingested data described in the dataset. */
    Tags?: Tag[];
}
export interface CreateInferenceSchedulerInput {
    /** A unique identifier for the request. If you do not set the client request token, Amazon Lookout for Equipment generates one. */
    ClientToken: string;
    /** Specifies configuration information for the input data for the inference scheduler, including delimiter, format, and dataset location. */
    DataInputConfiguration: InferenceInputConfiguration;
    /** Specifies configuration information for the output results for the inference scheduler, including the S3 location for the output. */
    DataOutputConfiguration: InferenceOutputConfiguration;
    /** How often data is uploaded to the source Amazon S3 bucket for the input data. The value chosen is the length of time between data uploads. For instance, if you select 5 minutes, Amazon Lookout for Equ */
    DataUploadFrequency: 'PT5M' | 'PT10M' | 'PT15M' | 'PT30M' | 'PT1H';
    /** The name of the inference scheduler being created. */
    InferenceSchedulerName: string;
    /** The name of the previously trained machine learning model being used to create the inference scheduler. */
    ModelName: string;
    /** The Amazon Resource Name (ARN) of a role with permission to access the data source being used for the inference. */
    RoleArn: string;
    /** The interval (in minutes) of planned delay at the start of each inference segment. For example, if inference is set to run every ten minutes, the delay is set to five minutes and the time is 09:08. Th */
    DataDelayOffsetInMinutes?: number;
    /** Provides the identifier of the KMS key used to encrypt inference scheduler data by Amazon Lookout for Equipment. */
    ServerSideKmsKeyId?: string;
    /** Any tags associated with the inference scheduler. */
    Tags?: Tag[];
}
export interface CreateLabelInput {
    /** A unique identifier for the request to create a label. If you do not set the client request token, Lookout for Equipment generates one. */
    ClientToken: string;
    /** The end time of the labeled event. */
    EndTime: string;
    /** The name of a group of labels. Data in this field will be retained for service usage. Follow best practices for the security of your data. */
    LabelGroupName: string;
    /** Indicates whether a labeled event represents an anomaly. */
    Rating: 'ANOMALY' | 'NO_ANOMALY' | 'NEUTRAL';
    /** The start time of the labeled event. */
    StartTime: string;
    /** Indicates that a label pertains to a particular piece of equipment. Data in this field will be retained for service usage. Follow best practices for the security of your data. */
    Equipment?: string;
    /** Provides additional information about the label. The fault code must be defined in the FaultCodes attribute of the label group. Data in this field will be retained for service usage. Follow best pract */
    FaultCode?: string;
    /** Metadata providing additional information about the label. Data in this field will be retained for service usage. Follow best practices for the security of your data. */
    Notes?: string;
}
export interface CreateLabelGroupInput {
    /** A unique identifier for the request to create a label group. If you do not set the client request token, Lookout for Equipment generates one. */
    ClientToken: string;
    /** Names a group of labels. Data in this field will be retained for service usage. Follow best practices for the security of your data. */
    LabelGroupName: string;
    /** The acceptable fault codes (indicating the type of anomaly associated with the label) that can be used with this label group. Data in this field will be retained for service usage. Follow best practic */
    FaultCodes?: string[];
    /** Tags that provide metadata about the label group you are creating. Data in this field will be retained for service usage. Follow best practices for the security of your data. */
    Tags?: Tag[];
}
export interface CreateModelInput {
    /** A unique identifier for the request. If you do not set the client request token, Amazon Lookout for Equipment generates one. */
    ClientToken: string;
    /** The name of the dataset for the machine learning model being created. */
    DatasetName: string;
    /** The name for the machine learning model to be created. */
    ModelName: string;
    /** The configuration is the TargetSamplingRate, which is the sampling rate of the data after post processing by Amazon Lookout for Equipment. For example, if you provide data that has been collected at a */
    DataPreProcessingConfiguration?: DataPreProcessingConfiguration;
    /** The data schema for the machine learning model being created. */
    DatasetSchema?: DatasetSchema;
    /** Indicates the time reference in the dataset that should be used to end the subset of evaluation data for the machine learning model. */
    EvaluationDataEndTime?: string;
    /** Indicates the time reference in the dataset that should be used to begin the subset of evaluation data for the machine learning model. */
    EvaluationDataStartTime?: string;
    /** The input configuration for the labels being used for the machine learning model that's being created. */
    LabelsInputConfiguration?: LabelsInputConfiguration;
    /** The Amazon S3 location where you want Amazon Lookout for Equipment to save the pointwise model diagnostics. You must also specify the RoleArn request parameter. */
    ModelDiagnosticsOutputConfiguration?: ModelDiagnosticsOutputConfiguration;
    /** Indicates that the asset associated with this sensor has been shut off. As long as this condition is met, Lookout for Equipment will not use data from this asset for training, evaluation, or inference */
    OffCondition?: string;
    /** The Amazon Resource Name (ARN) of a role with permission to access the data source being used to create the machine learning model. */
    RoleArn?: string;
    /** Provides the identifier of the KMS key used to encrypt model data by Amazon Lookout for Equipment. */
    ServerSideKmsKeyId?: string;
    /** Any tags associated with the machine learning model being created. */
    Tags?: Tag[];
    /** Indicates the time reference in the dataset that should be used to end the subset of training data for the machine learning model. */
    TrainingDataEndTime?: string;
    /** Indicates the time reference in the dataset that should be used to begin the subset of training data for the machine learning model. */
    TrainingDataStartTime?: string;
}
export interface CreateRetrainingSchedulerInput {
    /** A unique identifier for the request. If you do not set the client request token, Amazon Lookout for Equipment generates one. */
    ClientToken: string;
    /** The number of past days of data that will be used for retraining. */
    LookbackWindow: string;
    /** The name of the model to add the retraining scheduler to. */
    ModelName: string;
    /** This parameter uses the ISO 8601 standard to set the frequency at which you want retraining to occur in terms of Years, Months, and/or Days (note: other parameters like Time are not currently supporte */
    RetrainingFrequency: string;
    /** Indicates how the service will use new models. In MANAGED mode, new models will automatically be used for inference if they have better performance than the current model. In MANUAL mode, the new mode */
    PromoteMode?: 'MANAGED' | 'MANUAL';
    /** The start date for the retraining scheduler. Lookout for Equipment truncates the time you provide to the nearest UTC day. */
    RetrainingStartDate?: string;
}
export interface DeleteDatasetInput {
    /** The name of the dataset to be deleted. */
    DatasetName: string;
}
export interface DeleteInferenceSchedulerInput {
    /** The name of the inference scheduler to be deleted. */
    InferenceSchedulerName: string;
}
export interface DeleteLabelInput {
    /** The name of the label group that contains the label that you want to delete. Data in this field will be retained for service usage. Follow best practices for the security of your data. */
    LabelGroupName: string;
    /** The ID of the label that you want to delete. */
    LabelId: string;
}
export interface DeleteLabelGroupInput {
    /** The name of the label group that you want to delete. Data in this field will be retained for service usage. Follow best practices for the security of your data. */
    LabelGroupName: string;
}
export interface DeleteModelInput {
    /** The name of the machine learning model to be deleted. */
    ModelName: string;
}
export interface DeleteResourcePolicyInput {
    /** The Amazon Resource Name (ARN) of the resource for which the resource policy should be deleted. */
    ResourceArn: string;
}
export interface DeleteRetrainingSchedulerInput {
    /** The name of the model whose retraining scheduler you want to delete. */
    ModelName: string;
}
export interface DescribeDataIngestionJobInput {
    /** The job ID of the data ingestion job. */
    JobId: string;
}
export interface DescribeDatasetInput {
    /** The name of the dataset to be described. */
    DatasetName: string;
}
export interface DescribeInferenceSchedulerInput {
    /** The name of the inference scheduler being described. */
    InferenceSchedulerName: string;
}
export interface DescribeLabelInput {
    /** Returns the name of the group containing the label. */
    LabelGroupName: string;
    /** Returns the ID of the label. */
    LabelId: string;
}
export interface DescribeLabelGroupInput {
    /** Returns the name of the label group. */
    LabelGroupName: string;
}
export interface DescribeModelInput {
    /** The name of the machine learning model to be described. */
    ModelName: string;
}
export interface DescribeModelVersionInput {
    /** The name of the machine learning model that this version belongs to. */
    ModelName: string;
    /** The version of the machine learning model. */
    ModelVersion: number;
}
export interface DescribeResourcePolicyInput {
    /** The Amazon Resource Name (ARN) of the resource that is associated with the resource policy. */
    ResourceArn: string;
}
export interface DescribeRetrainingSchedulerInput {
    /** The name of the model that the retraining scheduler is attached to. */
    ModelName: string;
}
export interface ImportDatasetInput {
    /** A unique identifier for the request. If you do not set the client request token, Amazon Lookout for Equipment generates one. */
    ClientToken: string;
    /** The Amazon Resource Name (ARN) of the dataset to import. */
    SourceDatasetArn: string;
    /** The name of the machine learning dataset to be created. If the dataset already exists, Amazon Lookout for Equipment overwrites the existing dataset. If you don't specify this field, it is filled with  */
    DatasetName?: string;
    /** Provides the identifier of the KMS key key used to encrypt model data by Amazon Lookout for Equipment. */
    ServerSideKmsKeyId?: string;
    /** Any tags associated with the dataset to be created. */
    Tags?: Tag[];
}
export interface ImportModelVersionInput {
    /** A unique identifier for the request. If you do not set the client request token, Amazon Lookout for Equipment generates one. */
    ClientToken: string;
    /** The name of the dataset for the machine learning model being imported. */
    DatasetName: string;
    /** The Amazon Resource Name (ARN) of the model version to import. */
    SourceModelVersionArn: string;
    /** Indicates how to import the accumulated inference data when a model version is imported. The possible values are as follows: NO_IMPORT – Don't import the data. ADD_WHEN_EMPTY – Only import the data fr */
    InferenceDataImportStrategy?: 'NO_IMPORT' | 'ADD_WHEN_EMPTY' | 'OVERWRITE';
    LabelsInputConfiguration?: LabelsInputConfiguration;
    /** The name for the machine learning model to be created. If the model already exists, Amazon Lookout for Equipment creates a new version. If you do not specify this field, it is filled with the name of  */
    ModelName?: string;
    /** The Amazon Resource Name (ARN) of a role with permission to access the data source being used to create the machine learning model. */
    RoleArn?: string;
    /** Provides the identifier of the KMS key key used to encrypt model data by Amazon Lookout for Equipment. */
    ServerSideKmsKeyId?: string;
    /** The tags associated with the machine learning model to be created. */
    Tags?: Tag[];
}
export interface ListDataIngestionJobsInput {
    /** The name of the dataset being used for the data ingestion job. */
    DatasetName?: string;
    /** Specifies the maximum number of data ingestion jobs to list. */
    MaxResults?: number;
    /** An opaque pagination token indicating where to continue the listing of data ingestion jobs. */
    NextToken?: string;
    /** Indicates the status of the data ingestion job. */
    Status?: 'IN_PROGRESS' | 'SUCCESS' | 'FAILED' | 'IMPORT_IN_PROGRESS';
}
export interface ListDatasetsInput {
    /** The beginning of the name of the datasets to be listed. */
    DatasetNameBeginsWith?: string;
    /** Specifies the maximum number of datasets to list. */
    MaxResults?: number;
    /** An opaque pagination token indicating where to continue the listing of datasets. */
    NextToken?: string;
}
export interface ListInferenceEventsInput {
    /** The name of the inference scheduler for the inference events listed. */
    InferenceSchedulerName: string;
    /** Returns all the inference events with an end start time equal to or greater than less than the end time given. */
    IntervalEndTime: string;
    /** Lookout for Equipment will return all the inference events with an end time equal to or greater than the start time given. */
    IntervalStartTime: string;
    /** Specifies the maximum number of inference events to list. */
    MaxResults?: number;
    /** An opaque pagination token indicating where to continue the listing of inference events. */
    NextToken?: string;
}
export interface ListInferenceExecutionsInput {
    /** The name of the inference scheduler for the inference execution listed. */
    InferenceSchedulerName: string;
    /** The time reference in the inferenced dataset before which Amazon Lookout for Equipment stopped the inference execution. */
    DataEndTimeBefore?: string;
    /** The time reference in the inferenced dataset after which Amazon Lookout for Equipment started the inference execution. */
    DataStartTimeAfter?: string;
    /** Specifies the maximum number of inference executions to list. */
    MaxResults?: number;
    /** An opaque pagination token indicating where to continue the listing of inference executions. */
    NextToken?: string;
    /** The status of the inference execution. */
    Status?: 'IN_PROGRESS' | 'SUCCESS' | 'FAILED';
}
export interface ListInferenceSchedulersInput {
    /** The beginning of the name of the inference schedulers to be listed. */
    InferenceSchedulerNameBeginsWith?: string;
    /** Specifies the maximum number of inference schedulers to list. */
    MaxResults?: number;
    /** The name of the machine learning model used by the inference scheduler to be listed. */
    ModelName?: string;
    /** An opaque pagination token indicating where to continue the listing of inference schedulers. */
    NextToken?: string;
    /** Specifies the current status of the inference schedulers. */
    Status?: 'PENDING' | 'RUNNING' | 'STOPPING' | 'STOPPED';
}
export interface ListLabelGroupsInput {
    /** The beginning of the name of the label groups to be listed. */
    LabelGroupNameBeginsWith?: string;
    /** Specifies the maximum number of label groups to list. */
    MaxResults?: number;
    /** An opaque pagination token indicating where to continue the listing of label groups. */
    NextToken?: string;
}
export interface ListLabelsInput {
    /** Returns the name of the label group. */
    LabelGroupName: string;
    /** Lists the labels that pertain to a particular piece of equipment. */
    Equipment?: string;
    /** Returns labels with a particular fault code. */
    FaultCode?: string;
    /** Returns all labels with a start time earlier than the end time given. */
    IntervalEndTime?: string;
    /** Returns all the labels with a end time equal to or later than the start time given. */
    IntervalStartTime?: string;
    /** Specifies the maximum number of labels to list. */
    MaxResults?: number;
    /** An opaque pagination token indicating where to continue the listing of label groups. */
    NextToken?: string;
}
export interface ListModelsInput {
    /** The beginning of the name of the dataset of the machine learning models to be listed. */
    DatasetNameBeginsWith?: string;
    /** Specifies the maximum number of machine learning models to list. */
    MaxResults?: number;
    /** The beginning of the name of the machine learning models being listed. */
    ModelNameBeginsWith?: string;
    /** An opaque pagination token indicating where to continue the listing of machine learning models. */
    NextToken?: string;
    /** The status of the machine learning model. */
    Status?: 'IN_PROGRESS' | 'SUCCESS' | 'FAILED' | 'IMPORT_IN_PROGRESS';
}
export interface ListModelVersionsInput {
    /** Then name of the machine learning model for which the model versions are to be listed. */
    ModelName: string;
    /** Filter results to return all the model versions created before this time. */
    CreatedAtEndTime?: string;
    /** Filter results to return all the model versions created after this time. */
    CreatedAtStartTime?: string;
    /** Specifies the highest version of the model to return in the list. */
    MaxModelVersion?: number;
    /** Specifies the maximum number of machine learning model versions to list. */
    MaxResults?: number;
    /** Specifies the lowest version of the model to return in the list. */
    MinModelVersion?: number;
    /** If the total number of results exceeds the limit that the response can display, the response returns an opaque pagination token indicating where to continue the listing of machine learning model versi */
    NextToken?: string;
    /** Filter the results based on the way the model version was generated. */
    SourceType?: 'TRAINING' | 'RETRAINING' | 'IMPORT';
    /** Filter the results based on the current status of the model version. */
    Status?: 'IN_PROGRESS' | 'SUCCESS' | 'FAILED' | 'IMPORT_IN_PROGRESS' | 'CANCELED';
}
export interface ListRetrainingSchedulersInput {
    /** Specifies the maximum number of retraining schedulers to list. */
    MaxResults?: number;
    /** Specify this field to only list retraining schedulers whose machine learning models begin with the value you specify. */
    ModelNameBeginsWith?: string;
    /** If the number of results exceeds the maximum, a pagination token is returned. Use the token in the request to show the next page of retraining schedulers. */
    NextToken?: string;
    /** Specify this field to only list retraining schedulers whose status matches the value you specify. */
    Status?: 'PENDING' | 'RUNNING' | 'STOPPING' | 'STOPPED';
}
export interface ListSensorStatisticsInput {
    /** The name of the dataset associated with the list of Sensor Statistics. */
    DatasetName: string;
    /** The ingestion job id associated with the list of Sensor Statistics. To get sensor statistics for a particular ingestion job id, both dataset name and ingestion job id must be submitted as inputs. */
    IngestionJobId?: string;
    /** Specifies the maximum number of sensors for which to retrieve statistics. */
    MaxResults?: number;
    /** An opaque pagination token indicating where to continue the listing of sensor statistics. */
    NextToken?: string;
}
export interface ListTagsForResourceInput {
    /** The Amazon Resource Name (ARN) of the resource (such as the dataset or model) that is the focus of the ListTagsForResource operation. */
    ResourceArn: string;
}
export interface PutResourcePolicyInput {
    /** A unique identifier for the request. If you do not set the client request token, Amazon Lookout for Equipment generates one. */
    ClientToken: string;
    /** The Amazon Resource Name (ARN) of the resource for which the policy is being created. */
    ResourceArn: string;
    /** The JSON-formatted resource policy to create. */
    ResourcePolicy: string;
    /** A unique identifier for a revision of the resource policy. */
    PolicyRevisionId?: string;
}
export interface StartDataIngestionJobInput {
    /** A unique identifier for the request. If you do not set the client request token, Amazon Lookout for Equipment generates one. */
    ClientToken: string;
    /** The name of the dataset being used by the data ingestion job. */
    DatasetName: string;
    /** Specifies information for the input data for the data ingestion job, including dataset S3 location. */
    IngestionInputConfiguration: IngestionInputConfiguration;
    /** The Amazon Resource Name (ARN) of a role with permission to access the data source for the data ingestion job. */
    RoleArn: string;
}
export interface StartInferenceSchedulerInput {
    /** The name of the inference scheduler to be started. */
    InferenceSchedulerName: string;
}
export interface StartRetrainingSchedulerInput {
    /** The name of the model whose retraining scheduler you want to start. */
    ModelName: string;
}
export interface StopInferenceSchedulerInput {
    /** The name of the inference scheduler to be stopped. */
    InferenceSchedulerName: string;
}
export interface StopRetrainingSchedulerInput {
    /** The name of the model whose retraining scheduler you want to stop. */
    ModelName: string;
}
export interface TagResourceInput {
    /** The Amazon Resource Name (ARN) of the specific resource to which the tag should be associated. */
    ResourceArn: string;
    /** The tag or tags to be associated with a specific resource. Both the tag key and value are specified. */
    Tags: Tag[];
}
export interface UntagResourceInput {
    /** The Amazon Resource Name (ARN) of the resource to which the tag is currently associated. */
    ResourceArn: string;
    /** Specifies the key of the tag to be removed from a specified resource. */
    TagKeys: string[];
}
export interface UpdateActiveModelVersionInput {
    /** The name of the machine learning model for which the active model version is being set. */
    ModelName: string;
    /** The version of the machine learning model for which the active model version is being set. */
    ModelVersion: number;
}
export interface UpdateInferenceSchedulerInput {
    /** The name of the inference scheduler to be updated. */
    InferenceSchedulerName: string;
    /** A period of time (in minutes) by which inference on the data is delayed after the data starts. For instance, if you select an offset delay time of five minutes, inference will not begin on the data un */
    DataDelayOffsetInMinutes?: number;
    /** Specifies information for the input data for the inference scheduler, including delimiter, format, and dataset location. */
    DataInputConfiguration?: InferenceInputConfiguration;
    /** Specifies information for the output results from the inference scheduler, including the output S3 location. */
    DataOutputConfiguration?: InferenceOutputConfiguration;
    /** How often data is uploaded to the source S3 bucket for the input data. The value chosen is the length of time between data uploads. For instance, if you select 5 minutes, Amazon Lookout for Equipment  */
    DataUploadFrequency?: 'PT5M' | 'PT10M' | 'PT15M' | 'PT30M' | 'PT1H';
    /** The Amazon Resource Name (ARN) of a role with permission to access the data source for the inference scheduler. */
    RoleArn?: string;
}
export interface UpdateLabelGroupInput {
    /** The name of the label group to be updated. */
    LabelGroupName: string;
    /** Updates the code indicating the type of anomaly associated with the label. Data in this field will be retained for service usage. Follow best practices for the security of your data. */
    FaultCodes?: string[];
}
export interface UpdateModelInput {
    /** The name of the model to update. */
    ModelName: string;
    LabelsInputConfiguration?: LabelsInputConfiguration;
    /** The Amazon S3 location where you want Amazon Lookout for Equipment to save the pointwise model diagnostics for the model. You must also specify the RoleArn request parameter. */
    ModelDiagnosticsOutputConfiguration?: ModelDiagnosticsOutputConfiguration;
    /** The ARN of the model to update. */
    RoleArn?: string;
}
export interface UpdateRetrainingSchedulerInput {
    /** The name of the model whose retraining scheduler you want to update. */
    ModelName: string;
    /** The number of past days of data that will be used for retraining. */
    LookbackWindow?: string;
    /** Indicates how the service will use new models. In MANAGED mode, new models will automatically be used for inference if they have better performance than the current model. In MANUAL mode, the new mode */
    PromoteMode?: 'MANAGED' | 'MANUAL';
    /** This parameter uses the ISO 8601 standard to set the frequency at which you want retraining to occur in terms of Years, Months, and/or Days (note: other parameters like Time are not currently supporte */
    RetrainingFrequency?: string;
    /** The start date for the retraining scheduler. Lookout for Equipment truncates the time you provide to the nearest UTC day. */
    RetrainingStartDate?: string;
}
/** LookoutEquipment service binding for Step Functions SDK integrations. */
export declare class LookoutEquipment {
    constructor();
    createDataset<T>(params: CreateDatasetInput): Promise<T>;
    createInferenceScheduler<T>(params: CreateInferenceSchedulerInput): Promise<T>;
    createLabel<T>(params: CreateLabelInput): Promise<T>;
    createLabelGroup<T>(params: CreateLabelGroupInput): Promise<T>;
    createModel<T>(params: CreateModelInput): Promise<T>;
    createRetrainingScheduler<T>(params: CreateRetrainingSchedulerInput): Promise<T>;
    deleteDataset<T>(params: DeleteDatasetInput): Promise<T>;
    deleteInferenceScheduler<T>(params: DeleteInferenceSchedulerInput): Promise<T>;
    deleteLabel<T>(params: DeleteLabelInput): Promise<T>;
    deleteLabelGroup<T>(params: DeleteLabelGroupInput): Promise<T>;
    deleteModel<T>(params: DeleteModelInput): Promise<T>;
    deleteResourcePolicy<T>(params: DeleteResourcePolicyInput): Promise<T>;
    deleteRetrainingScheduler<T>(params: DeleteRetrainingSchedulerInput): Promise<T>;
    describeDataIngestionJob<T>(params: DescribeDataIngestionJobInput): Promise<T>;
    describeDataset<T>(params: DescribeDatasetInput): Promise<T>;
    describeInferenceScheduler<T>(params: DescribeInferenceSchedulerInput): Promise<T>;
    describeLabel<T>(params: DescribeLabelInput): Promise<T>;
    describeLabelGroup<T>(params: DescribeLabelGroupInput): Promise<T>;
    describeModel<T>(params: DescribeModelInput): Promise<T>;
    describeModelVersion<T>(params: DescribeModelVersionInput): Promise<T>;
    describeResourcePolicy<T>(params: DescribeResourcePolicyInput): Promise<T>;
    describeRetrainingScheduler<T>(params: DescribeRetrainingSchedulerInput): Promise<T>;
    importDataset<T>(params: ImportDatasetInput): Promise<T>;
    importModelVersion<T>(params: ImportModelVersionInput): Promise<T>;
    listDataIngestionJobs<T>(params: ListDataIngestionJobsInput): Promise<T>;
    listDatasets<T>(params: ListDatasetsInput): Promise<T>;
    listInferenceEvents<T>(params: ListInferenceEventsInput): Promise<T>;
    listInferenceExecutions<T>(params: ListInferenceExecutionsInput): Promise<T>;
    listInferenceSchedulers<T>(params: ListInferenceSchedulersInput): Promise<T>;
    listLabelGroups<T>(params: ListLabelGroupsInput): Promise<T>;
    listLabels<T>(params: ListLabelsInput): Promise<T>;
    listModels<T>(params: ListModelsInput): Promise<T>;
    listModelVersions<T>(params: ListModelVersionsInput): Promise<T>;
    listRetrainingSchedulers<T>(params: ListRetrainingSchedulersInput): Promise<T>;
    listSensorStatistics<T>(params: ListSensorStatisticsInput): Promise<T>;
    listTagsForResource<T>(params: ListTagsForResourceInput): Promise<T>;
    putResourcePolicy<T>(params: PutResourcePolicyInput): Promise<T>;
    startDataIngestionJob<T>(params: StartDataIngestionJobInput): Promise<T>;
    startInferenceScheduler<T>(params: StartInferenceSchedulerInput): Promise<T>;
    startRetrainingScheduler<T>(params: StartRetrainingSchedulerInput): Promise<T>;
    stopInferenceScheduler<T>(params: StopInferenceSchedulerInput): Promise<T>;
    stopRetrainingScheduler<T>(params: StopRetrainingSchedulerInput): Promise<T>;
    tagResource<T>(params: TagResourceInput): Promise<T>;
    untagResource<T>(params: UntagResourceInput): Promise<T>;
    updateActiveModelVersion<T>(params: UpdateActiveModelVersionInput): Promise<T>;
    updateInferenceScheduler<T>(params: UpdateInferenceSchedulerInput): Promise<T>;
    updateLabelGroup<T>(params: UpdateLabelGroupInput): Promise<T>;
    updateModel<T>(params: UpdateModelInput): Promise<T>;
    updateRetrainingScheduler<T>(params: UpdateRetrainingSchedulerInput): Promise<T>;
}
//# sourceMappingURL=LookoutEquipment.d.ts.map