/**
 * Copyright 2015 Google Inc. All Rights Reserved.
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *      http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */
import { AxiosPromise } from 'axios';
import { GoogleApis } from '../..';
import { BodyResponseCallback, GlobalOptions, MethodOptions } from '../../lib/api';
/**
 * Prediction API
 *
 * Lets you access a cloud hosted machine learning service that makes it easy to
 * build smart apps
 *
 * @example
 * const google = require('googleapis');
 * const prediction = google.prediction('v1.4');
 *
 * @namespace prediction
 * @type {Function}
 * @version v1.4
 * @variation v1.4
 * @param {object=} options Options for Prediction
 */
export declare class Prediction {
    _options: GlobalOptions;
    google: GoogleApis;
    root: this;
    hostedmodels: Resource$Hostedmodels;
    trainedmodels: Resource$Trainedmodels;
    constructor(options: GlobalOptions, google: GoogleApis);
    getRoot(): this;
}
export interface Schema$Input {
    /**
     * Input to the model for a prediction
     */
    input: any;
}
export interface Schema$Output {
    /**
     * The unique name for the predictive model.
     */
    id: string;
    /**
     * What kind of resource this is.
     */
    kind: string;
    /**
     * The most likely class label [Categorical models only].
     */
    outputLabel: string;
    /**
     * A list of class labels with their estimated probabilities [Categorical
     * models only].
     */
    outputMulti: any[];
    /**
     * The estimated regression value [Regression models only].
     */
    outputValue: number;
    /**
     * A URL to re-request this resource.
     */
    selfLink: string;
}
export interface Schema$Training {
    /**
     * Data Analysis.
     */
    dataAnalysis: any;
    /**
     * The unique name for the predictive model.
     */
    id: string;
    /**
     * What kind of resource this is.
     */
    kind: string;
    /**
     * Model metadata.
     */
    modelInfo: any;
    /**
     * A URL to re-request this resource.
     */
    selfLink: string;
    /**
     * Google storage location of the training data file.
     */
    storageDataLocation: string;
    /**
     * Google storage location of the preprocessing pmml file.
     */
    storagePMMLLocation: string;
    /**
     * Google storage location of the pmml model file.
     */
    storagePMMLModelLocation: string;
    /**
     * The current status of the training job. This can be one of following:
     * RUNNING; DONE; ERROR; ERROR: TRAINING JOB NOT FOUND
     */
    trainingStatus: string;
    /**
     * A class weighting function, which allows the importance weights for class
     * labels to be specified [Categorical models only].
     */
    utility: any[];
}
export interface Schema$Update {
    /**
     * The input features for this instance
     */
    csvInstance: any[];
    /**
     * The class label of this instance
     */
    label: string;
    /**
     * The generic output value - could be regression value or class label
     */
    output: string;
}
export declare class Resource$Hostedmodels {
    root: Prediction;
    constructor(root: Prediction);
    getRoot(): Prediction;
    /**
     * prediction.hostedmodels.predict
     * @desc Submit input and request an output against a hosted model.
     * @alias prediction.hostedmodels.predict
     * @memberOf! ()
     *
     * @param {object} params Parameters for request
     * @param {string} params.hostedModelName The name of a hosted model.
     * @param {().Input} params.resource Request body data
     * @param {object} [options] Optionally override request options, such as `url`, `method`, and `encoding`.
     * @param {callback} callback The callback that handles the response.
     * @return {object} Request object
     */
    predict(params?: any, options?: MethodOptions): AxiosPromise<Schema$Output>;
    predict(params?: any, options?: MethodOptions | BodyResponseCallback<Schema$Output>, callback?: BodyResponseCallback<Schema$Output>): void;
}
export declare class Resource$Trainedmodels {
    root: Prediction;
    constructor(root: Prediction);
    getRoot(): Prediction;
    /**
     * prediction.trainedmodels.delete
     * @desc Delete a trained model.
     * @alias prediction.trainedmodels.delete
     * @memberOf! ()
     *
     * @param {object} params Parameters for request
     * @param {string} params.id The unique name for the predictive model.
     * @param {object} [options] Optionally override request options, such as `url`, `method`, and `encoding`.
     * @param {callback} callback The callback that handles the response.
     * @return {object} Request object
     */
    delete(params?: any, options?: MethodOptions): AxiosPromise<void>;
    delete(params?: any, options?: MethodOptions | BodyResponseCallback<void>, callback?: BodyResponseCallback<void>): void;
    /**
     * prediction.trainedmodels.get
     * @desc Check training status of your model.
     * @alias prediction.trainedmodels.get
     * @memberOf! ()
     *
     * @param {object} params Parameters for request
     * @param {string} params.id The unique name for the predictive model.
     * @param {object} [options] Optionally override request options, such as `url`, `method`, and `encoding`.
     * @param {callback} callback The callback that handles the response.
     * @return {object} Request object
     */
    get(params?: any, options?: MethodOptions): AxiosPromise<Schema$Training>;
    get(params?: any, options?: MethodOptions | BodyResponseCallback<Schema$Training>, callback?: BodyResponseCallback<Schema$Training>): void;
    /**
     * prediction.trainedmodels.insert
     * @desc Begin training your model.
     * @alias prediction.trainedmodels.insert
     * @memberOf! ()
     *
     * @param {object} params Parameters for request
     * @param {().Training} params.resource Request body data
     * @param {object} [options] Optionally override request options, such as `url`, `method`, and `encoding`.
     * @param {callback} callback The callback that handles the response.
     * @return {object} Request object
     */
    insert(params?: any, options?: MethodOptions): AxiosPromise<Schema$Training>;
    insert(params?: any, options?: MethodOptions | BodyResponseCallback<Schema$Training>, callback?: BodyResponseCallback<Schema$Training>): void;
    /**
     * prediction.trainedmodels.predict
     * @desc Submit model id and request a prediction
     * @alias prediction.trainedmodels.predict
     * @memberOf! ()
     *
     * @param {object} params Parameters for request
     * @param {string} params.id The unique name for the predictive model.
     * @param {().Input} params.resource Request body data
     * @param {object} [options] Optionally override request options, such as `url`, `method`, and `encoding`.
     * @param {callback} callback The callback that handles the response.
     * @return {object} Request object
     */
    predict(params?: any, options?: MethodOptions): AxiosPromise<Schema$Output>;
    predict(params?: any, options?: MethodOptions | BodyResponseCallback<Schema$Output>, callback?: BodyResponseCallback<Schema$Output>): void;
    /**
     * prediction.trainedmodels.update
     * @desc Add new data to a trained model.
     * @alias prediction.trainedmodels.update
     * @memberOf! ()
     *
     * @param {object} params Parameters for request
     * @param {string} params.id The unique name for the predictive model.
     * @param {().Update} params.resource Request body data
     * @param {object} [options] Optionally override request options, such as `url`, `method`, and `encoding`.
     * @param {callback} callback The callback that handles the response.
     * @return {object} Request object
     */
    update(params?: any, options?: MethodOptions): AxiosPromise<Schema$Training>;
    update(params?: any, options?: MethodOptions | BodyResponseCallback<Schema$Training>, callback?: BodyResponseCallback<Schema$Training>): void;
}