import type { MetadataBearer as __MetadataBearer } from "@smithy/types";
import type { CreateExplainabilityRequest, CreateExplainabilityResponse } from "../models/models_0";
/**
 * @public
 */
export type { __MetadataBearer };
/**
 * @public
 *
 * The input for {@link CreateExplainabilityCommand}.
 */
export interface CreateExplainabilityCommandInput extends CreateExplainabilityRequest {
}
/**
 * @public
 *
 * The output of {@link CreateExplainabilityCommand}.
 */
export interface CreateExplainabilityCommandOutput extends CreateExplainabilityResponse, __MetadataBearer {
}
declare const CreateExplainabilityCommand_base: {
    new (input: CreateExplainabilityCommandInput): import("@smithy/core/client").CommandImpl<CreateExplainabilityCommandInput, CreateExplainabilityCommandOutput, import("..").ForecastClientResolvedConfig, import("..").ServiceInputTypes, import("..").ServiceOutputTypes>;
    new (input: CreateExplainabilityCommandInput): import("@smithy/core/client").CommandImpl<CreateExplainabilityCommandInput, CreateExplainabilityCommandOutput, import("..").ForecastClientResolvedConfig, import("..").ServiceInputTypes, import("..").ServiceOutputTypes>;
    getEndpointParameterInstructions(): import("@smithy/types").EndpointParameterInstructions;
};
/**
 * <note>
 *             <p>Explainability is only available for Forecasts and Predictors generated from an
 *                 AutoPredictor (<a>CreateAutoPredictor</a>)</p>
 *          </note>
 *          <p>Creates an Amazon Forecast Explainability.</p>
 *          <p>Explainability helps you better understand how the attributes in your datasets impact
 *             forecast. Amazon Forecast uses a metric called Impact scores to quantify the relative
 *             impact of each attribute and determine whether they increase or decrease forecast
 *             values.</p>
 *          <p>To enable Forecast Explainability, your predictor must include at least one of the
 *             following: related time series, item metadata, or additional datasets like Holidays and
 *             the Weather Index.</p>
 *          <p>CreateExplainability accepts either a Predictor ARN or Forecast ARN. To receive
 *             aggregated Impact scores for all time series and time points in your datasets, provide a
 *             Predictor ARN. To receive Impact scores for specific time series and time points,
 *             provide a Forecast ARN.</p>
 *          <p>
 *             <b>CreateExplainability with a Predictor ARN</b>
 *          </p>
 *          <note>
 *             <p>You can only have one Explainability resource per predictor. If you already
 *                 enabled <code>ExplainPredictor</code> in <a>CreateAutoPredictor</a>, that
 *                 predictor already has an Explainability resource.</p>
 *          </note>
 *          <p>The following parameters are required when providing a Predictor ARN:</p>
 *          <ul>
 *             <li>
 *                <p>
 *                   <code>ExplainabilityName</code> - A unique name for the Explainability.</p>
 *             </li>
 *             <li>
 *                <p>
 *                   <code>ResourceArn</code> - The Arn of the predictor.</p>
 *             </li>
 *             <li>
 *                <p>
 *                   <code>TimePointGranularity</code> - Must be set to “ALL”.</p>
 *             </li>
 *             <li>
 *                <p>
 *                   <code>TimeSeriesGranularity</code> - Must be set to “ALL”.</p>
 *             </li>
 *          </ul>
 *          <p>Do not specify a value for the following parameters:</p>
 *          <ul>
 *             <li>
 *                <p>
 *                   <code>DataSource</code> - Only valid when TimeSeriesGranularity is
 *                     “SPECIFIC”.</p>
 *             </li>
 *             <li>
 *                <p>
 *                   <code>Schema</code> - Only valid when TimeSeriesGranularity is
 *                     “SPECIFIC”.</p>
 *             </li>
 *             <li>
 *                <p>
 *                   <code>StartDateTime</code> - Only valid when TimePointGranularity is
 *                     “SPECIFIC”.</p>
 *             </li>
 *             <li>
 *                <p>
 *                   <code>EndDateTime</code> - Only valid when TimePointGranularity is
 *                     “SPECIFIC”.</p>
 *             </li>
 *          </ul>
 *          <p>
 *             <b>CreateExplainability with a Forecast ARN</b>
 *          </p>
 *          <note>
 *             <p>You can specify a maximum of 50 time series and 500 time points.</p>
 *          </note>
 *          <p>The following parameters are required when providing a Predictor ARN:</p>
 *          <ul>
 *             <li>
 *                <p>
 *                   <code>ExplainabilityName</code> - A unique name for the Explainability.</p>
 *             </li>
 *             <li>
 *                <p>
 *                   <code>ResourceArn</code> - The Arn of the forecast.</p>
 *             </li>
 *             <li>
 *                <p>
 *                   <code>TimePointGranularity</code> - Either “ALL” or “SPECIFIC”.</p>
 *             </li>
 *             <li>
 *                <p>
 *                   <code>TimeSeriesGranularity</code> - Either “ALL” or “SPECIFIC”.</p>
 *             </li>
 *          </ul>
 *          <p>If you set TimeSeriesGranularity to “SPECIFIC”, you must also provide the
 *             following:</p>
 *          <ul>
 *             <li>
 *                <p>
 *                   <code>DataSource</code> - The S3 location of the CSV file specifying your time
 *                     series.</p>
 *             </li>
 *             <li>
 *                <p>
 *                   <code>Schema</code> - The Schema defines the attributes and attribute types
 *                     listed in the Data Source.</p>
 *             </li>
 *          </ul>
 *          <p>If you set TimePointGranularity to “SPECIFIC”, you must also provide the
 *             following:</p>
 *          <ul>
 *             <li>
 *                <p>
 *                   <code>StartDateTime</code> - The first timestamp in the range of time
 *                     points.</p>
 *             </li>
 *             <li>
 *                <p>
 *                   <code>EndDateTime</code> - The last timestamp in the range of time
 *                     points.</p>
 *             </li>
 *          </ul>
 * @example
 * Use a bare-bones client and the command you need to make an API call.
 * ```javascript
 * import { ForecastClient, CreateExplainabilityCommand } from "@aws-sdk/client-forecast"; // ES Modules import
 * // const { ForecastClient, CreateExplainabilityCommand } = require("@aws-sdk/client-forecast"); // CommonJS import
 * // import type { ForecastClientConfig } from "@aws-sdk/client-forecast";
 * const config = {}; // type is ForecastClientConfig
 * const client = new ForecastClient(config);
 * const input = { // CreateExplainabilityRequest
 *   ExplainabilityName: "STRING_VALUE", // required
 *   ResourceArn: "STRING_VALUE", // required
 *   ExplainabilityConfig: { // ExplainabilityConfig
 *     TimeSeriesGranularity: "ALL" || "SPECIFIC", // required
 *     TimePointGranularity: "ALL" || "SPECIFIC", // required
 *   },
 *   DataSource: { // DataSource
 *     S3Config: { // S3Config
 *       Path: "STRING_VALUE", // required
 *       RoleArn: "STRING_VALUE", // required
 *       KMSKeyArn: "STRING_VALUE",
 *     },
 *   },
 *   Schema: { // Schema
 *     Attributes: [ // SchemaAttributes
 *       { // SchemaAttribute
 *         AttributeName: "STRING_VALUE",
 *         AttributeType: "string" || "integer" || "float" || "timestamp" || "geolocation",
 *       },
 *     ],
 *   },
 *   EnableVisualization: true || false,
 *   StartDateTime: "STRING_VALUE",
 *   EndDateTime: "STRING_VALUE",
 *   Tags: [ // Tags
 *     { // Tag
 *       Key: "STRING_VALUE", // required
 *       Value: "STRING_VALUE", // required
 *     },
 *   ],
 * };
 * const command = new CreateExplainabilityCommand(input);
 * const response = await client.send(command);
 * // { // CreateExplainabilityResponse
 * //   ExplainabilityArn: "STRING_VALUE",
 * // };
 *
 * ```
 *
 * @param CreateExplainabilityCommandInput - {@link CreateExplainabilityCommandInput}
 * @returns {@link CreateExplainabilityCommandOutput}
 * @see {@link CreateExplainabilityCommandInput} for command's `input` shape.
 * @see {@link CreateExplainabilityCommandOutput} for command's `response` shape.
 * @see {@link ForecastClientResolvedConfig | config} for ForecastClient's `config` shape.
 *
 * @throws {@link InvalidInputException} (client fault)
 *  <p>We can't process the request because it includes an invalid value or a value that exceeds
 *       the valid range.</p>
 *
 * @throws {@link LimitExceededException} (client fault)
 *  <p>The limit on the number of resources per account has been exceeded.</p>
 *
 * @throws {@link ResourceAlreadyExistsException} (client fault)
 *  <p>There is already a resource with this name. Try again with a different name.</p>
 *
 * @throws {@link ResourceInUseException} (client fault)
 *  <p>The specified resource is in use.</p>
 *
 * @throws {@link ResourceNotFoundException} (client fault)
 *  <p>We can't find a resource with that Amazon Resource Name (ARN). Check the ARN and try
 *       again.</p>
 *
 * @throws {@link ForecastServiceException}
 * <p>Base exception class for all service exceptions from Forecast service.</p>
 *
 *
 * @public
 */
export declare class CreateExplainabilityCommand extends CreateExplainabilityCommand_base {
    /** @internal type navigation helper, not in runtime. */
    protected static __types: {
        api: {
            input: CreateExplainabilityRequest;
            output: CreateExplainabilityResponse;
        };
        sdk: {
            input: CreateExplainabilityCommandInput;
            output: CreateExplainabilityCommandOutput;
        };
    };
}