import type { MetadataBearer as __MetadataBearer } from "@smithy/types";
import type { UpdateEvaluationInput, UpdateEvaluationOutput } from "../models/models_0";
/**
 * @public
 */
export type { __MetadataBearer };
/**
 * @public
 *
 * The input for {@link UpdateEvaluationCommand}.
 */
export interface UpdateEvaluationCommandInput extends UpdateEvaluationInput {
}
/**
 * @public
 *
 * The output of {@link UpdateEvaluationCommand}.
 */
export interface UpdateEvaluationCommandOutput extends UpdateEvaluationOutput, __MetadataBearer {
}
declare const UpdateEvaluationCommand_base: {
    new (input: UpdateEvaluationCommandInput): import("@smithy/core/client").CommandImpl<UpdateEvaluationCommandInput, UpdateEvaluationCommandOutput, import("..").MachineLearningClientResolvedConfig, import("..").ServiceInputTypes, import("..").ServiceOutputTypes>;
    new (input: UpdateEvaluationCommandInput): import("@smithy/core/client").CommandImpl<UpdateEvaluationCommandInput, UpdateEvaluationCommandOutput, import("..").MachineLearningClientResolvedConfig, import("..").ServiceInputTypes, import("..").ServiceOutputTypes>;
    getEndpointParameterInstructions(): import("@smithy/types").EndpointParameterInstructions;
};
/**
 * <p>Updates the <code>EvaluationName</code> of an <code>Evaluation</code>.</p>
 *         <p>You can use the <code>GetEvaluation</code> operation to view the contents of the updated data element.</p>
 * @example
 * Use a bare-bones client and the command you need to make an API call.
 * ```javascript
 * import { MachineLearningClient, UpdateEvaluationCommand } from "@aws-sdk/client-machine-learning"; // ES Modules import
 * // const { MachineLearningClient, UpdateEvaluationCommand } = require("@aws-sdk/client-machine-learning"); // CommonJS import
 * // import type { MachineLearningClientConfig } from "@aws-sdk/client-machine-learning";
 * const config = {}; // type is MachineLearningClientConfig
 * const client = new MachineLearningClient(config);
 * const input = { // UpdateEvaluationInput
 *   EvaluationId: "STRING_VALUE", // required
 *   EvaluationName: "STRING_VALUE", // required
 * };
 * const command = new UpdateEvaluationCommand(input);
 * const response = await client.send(command);
 * // { // UpdateEvaluationOutput
 * //   EvaluationId: "STRING_VALUE",
 * // };
 *
 * ```
 *
 * @param UpdateEvaluationCommandInput - {@link UpdateEvaluationCommandInput}
 * @returns {@link UpdateEvaluationCommandOutput}
 * @see {@link UpdateEvaluationCommandInput} for command's `input` shape.
 * @see {@link UpdateEvaluationCommandOutput} for command's `response` shape.
 * @see {@link MachineLearningClientResolvedConfig | config} for MachineLearningClient's `config` shape.
 *
 * @throws {@link InternalServerException} (server fault)
 *  <p>An error on the server occurred when trying to process a request.</p>
 *
 * @throws {@link InvalidInputException} (client fault)
 *  <p>An error on the client occurred. Typically, the cause is an invalid input value.</p>
 *
 * @throws {@link ResourceNotFoundException} (client fault)
 *  <p>A specified resource cannot be located.</p>
 *
 * @throws {@link MachineLearningServiceException}
 * <p>Base exception class for all service exceptions from MachineLearning service.</p>
 *
 *
 * @public
 */
export declare class UpdateEvaluationCommand extends UpdateEvaluationCommand_base {
    /** @internal type navigation helper, not in runtime. */
    protected static __types: {
        api: {
            input: UpdateEvaluationInput;
            output: UpdateEvaluationOutput;
        };
        sdk: {
            input: UpdateEvaluationCommandInput;
            output: UpdateEvaluationCommandOutput;
        };
    };
}