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GotPPay
417
backend/node_modules/googleapis/apis/prediction/v1.5.ts
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417
backend/node_modules/googleapis/apis/prediction/v1.5.ts
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/**
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* Copyright 2015 Google Inc. All Rights Reserved.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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/* jshint maxlen: false */
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import createAPIRequest from '../../lib/apirequest';
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/**
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* Prediction API
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*
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* Lets you access a cloud hosted machine learning service that makes it easy to build smart apps
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*
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* @example
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* const google = require('googleapis');
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* const prediction = google.prediction('v1.5');
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*
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* @namespace prediction
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* @type {Function}
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* @version v1.5
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* @variation v1.5
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* @param {object=} options Options for Prediction
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*/
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function Prediction(options) { // eslint-disable-line
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const self = this;
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self._options = options || {};
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self.hostedmodels = {
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/**
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* prediction.hostedmodels.predict
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*
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* @desc Submit input and request an output against a hosted model.
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*
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* @alias prediction.hostedmodels.predict
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* @memberOf! prediction(v1.5)
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*
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* @param {object} params Parameters for request
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* @param {string} params.hostedModelName The name of a hosted model.
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* @param {prediction(v1.5).Input} params.resource Request body data
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* @param {object} [options] Optionally override request options, such as `url`, `method`, and `encoding`.
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* @param {callback} callback The callback that handles the response.
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* @return {object} Request object
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*/
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predict: function (params, options, callback) {
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if (typeof options === 'function') {
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callback = options;
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options = {};
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}
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options || (options = {});
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const rootUrl = options.rootUrl || 'https://www.googleapis.com/';
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const parameters = {
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options: Object.assign({
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url: (rootUrl + '/prediction/v1.5/hostedmodels/{hostedModelName}/predict').replace(/([^:]\/)\/+/g, '$1'),
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method: 'POST'
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}, options),
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params: params,
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requiredParams: ['hostedModelName'],
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pathParams: ['hostedModelName'],
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context: self
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};
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return createAPIRequest(parameters, callback);
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}
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};
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self.trainedmodels = {
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/**
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* prediction.trainedmodels.analyze
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*
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* @desc Get analysis of the model and the data the model was trained on.
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*
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* @alias prediction.trainedmodels.analyze
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* @memberOf! prediction(v1.5)
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*
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* @param {object} params Parameters for request
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* @param {string} params.id The unique name for the predictive model.
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* @param {object} [options] Optionally override request options, such as `url`, `method`, and `encoding`.
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* @param {callback} callback The callback that handles the response.
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* @return {object} Request object
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*/
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analyze: function (params, options, callback) {
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if (typeof options === 'function') {
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callback = options;
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options = {};
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}
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options || (options = {});
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const rootUrl = options.rootUrl || 'https://www.googleapis.com/';
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const parameters = {
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options: Object.assign({
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url: (rootUrl + '/prediction/v1.5/trainedmodels/{id}/analyze').replace(/([^:]\/)\/+/g, '$1'),
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method: 'GET'
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}, options),
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params: params,
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requiredParams: ['id'],
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pathParams: ['id'],
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context: self
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};
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return createAPIRequest(parameters, callback);
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},
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/**
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* prediction.trainedmodels.delete
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*
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* @desc Delete a trained model.
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*
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* @alias prediction.trainedmodels.delete
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* @memberOf! prediction(v1.5)
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*
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* @param {object} params Parameters for request
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* @param {string} params.id The unique name for the predictive model.
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* @param {object} [options] Optionally override request options, such as `url`, `method`, and `encoding`.
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* @param {callback} callback The callback that handles the response.
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* @return {object} Request object
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*/
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delete: function (params, options, callback) {
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if (typeof options === 'function') {
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callback = options;
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options = {};
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}
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options || (options = {});
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const rootUrl = options.rootUrl || 'https://www.googleapis.com/';
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const parameters = {
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options: Object.assign({
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url: (rootUrl + '/prediction/v1.5/trainedmodels/{id}').replace(/([^:]\/)\/+/g, '$1'),
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method: 'DELETE'
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}, options),
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params: params,
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requiredParams: ['id'],
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pathParams: ['id'],
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context: self
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};
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return createAPIRequest(parameters, callback);
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},
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/**
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* prediction.trainedmodels.get
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*
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* @desc Check training status of your model.
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*
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* @alias prediction.trainedmodels.get
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* @memberOf! prediction(v1.5)
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*
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* @param {object} params Parameters for request
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* @param {string} params.id The unique name for the predictive model.
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* @param {object} [options] Optionally override request options, such as `url`, `method`, and `encoding`.
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* @param {callback} callback The callback that handles the response.
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* @return {object} Request object
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*/
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get: function (params, options, callback) {
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if (typeof options === 'function') {
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callback = options;
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options = {};
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}
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options || (options = {});
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const rootUrl = options.rootUrl || 'https://www.googleapis.com/';
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const parameters = {
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options: Object.assign({
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url: (rootUrl + '/prediction/v1.5/trainedmodels/{id}').replace(/([^:]\/)\/+/g, '$1'),
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method: 'GET'
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}, options),
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params: params,
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requiredParams: ['id'],
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pathParams: ['id'],
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context: self
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};
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return createAPIRequest(parameters, callback);
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},
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/**
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* prediction.trainedmodels.insert
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*
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* @desc Begin training your model.
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*
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* @alias prediction.trainedmodels.insert
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* @memberOf! prediction(v1.5)
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*
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* @param {object} params Parameters for request
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* @param {prediction(v1.5).Training} params.resource Request body data
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* @param {object} [options] Optionally override request options, such as `url`, `method`, and `encoding`.
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* @param {callback} callback The callback that handles the response.
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* @return {object} Request object
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*/
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insert: function (params, options, callback) {
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if (typeof options === 'function') {
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callback = options;
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options = {};
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}
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options || (options = {});
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const rootUrl = options.rootUrl || 'https://www.googleapis.com/';
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const parameters = {
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options: Object.assign({
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url: (rootUrl + '/prediction/v1.5/trainedmodels').replace(/([^:]\/)\/+/g, '$1'),
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method: 'POST'
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}, options),
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params: params,
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requiredParams: [],
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pathParams: [],
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context: self
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};
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return createAPIRequest(parameters, callback);
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},
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/**
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* prediction.trainedmodels.list
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*
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* @desc List available models.
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*
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* @alias prediction.trainedmodels.list
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* @memberOf! prediction(v1.5)
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*
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* @param {object=} params Parameters for request
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* @param {integer=} params.maxResults Maximum number of results to return
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* @param {string=} params.pageToken Pagination token
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* @param {object} [options] Optionally override request options, such as `url`, `method`, and `encoding`.
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* @param {callback} callback The callback that handles the response.
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* @return {object} Request object
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*/
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list: function (params, options, callback) {
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if (typeof options === 'function') {
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callback = options;
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options = {};
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}
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options || (options = {});
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const rootUrl = options.rootUrl || 'https://www.googleapis.com/';
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const parameters = {
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options: Object.assign({
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url: (rootUrl + '/prediction/v1.5/trainedmodels/list').replace(/([^:]\/)\/+/g, '$1'),
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method: 'GET'
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}, options),
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params: params,
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requiredParams: [],
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pathParams: [],
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context: self
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};
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return createAPIRequest(parameters, callback);
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},
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/**
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* prediction.trainedmodels.predict
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*
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* @desc Submit model id and request a prediction.
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*
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* @alias prediction.trainedmodels.predict
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* @memberOf! prediction(v1.5)
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*
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* @param {object} params Parameters for request
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* @param {string} params.id The unique name for the predictive model.
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* @param {prediction(v1.5).Input} params.resource Request body data
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* @param {object} [options] Optionally override request options, such as `url`, `method`, and `encoding`.
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* @param {callback} callback The callback that handles the response.
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* @return {object} Request object
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*/
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predict: function (params, options, callback) {
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if (typeof options === 'function') {
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callback = options;
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options = {};
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}
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options || (options = {});
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const rootUrl = options.rootUrl || 'https://www.googleapis.com/';
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const parameters = {
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options: Object.assign({
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url: (rootUrl + '/prediction/v1.5/trainedmodels/{id}/predict').replace(/([^:]\/)\/+/g, '$1'),
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method: 'POST'
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}, options),
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params: params,
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requiredParams: ['id'],
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pathParams: ['id'],
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context: self
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};
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return createAPIRequest(parameters, callback);
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},
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/**
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* prediction.trainedmodels.update
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*
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* @desc Add new data to a trained model.
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*
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* @alias prediction.trainedmodels.update
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* @memberOf! prediction(v1.5)
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*
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* @param {object} params Parameters for request
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* @param {string} params.id The unique name for the predictive model.
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* @param {prediction(v1.5).Update} params.resource Request body data
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* @param {object} [options] Optionally override request options, such as `url`, `method`, and `encoding`.
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* @param {callback} callback The callback that handles the response.
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* @return {object} Request object
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*/
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update: function (params, options, callback) {
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if (typeof options === 'function') {
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callback = options;
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options = {};
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}
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options || (options = {});
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const rootUrl = options.rootUrl || 'https://www.googleapis.com/';
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const parameters = {
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options: Object.assign({
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url: (rootUrl + '/prediction/v1.5/trainedmodels/{id}').replace(/([^:]\/)\/+/g, '$1'),
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method: 'PUT'
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}, options),
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params: params,
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requiredParams: ['id'],
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pathParams: ['id'],
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context: self
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};
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return createAPIRequest(parameters, callback);
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}
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};
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}
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/**
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* @typedef Analyze
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* @memberOf! prediction(v1.5)
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* @type object
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* @property {object} dataDescription Description of the data the model was trained on.
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* @property {object[]} errors List of errors with the data.
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* @property {string} id The unique name for the predictive model.
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* @property {string} kind What kind of resource this is.
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* @property {object} modelDescription Description of the model.
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* @property {string} selfLink A URL to re-request this resource.
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*/
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/**
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* @typedef Input
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* @memberOf! prediction(v1.5)
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* @type object
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* @property {object} input Input to the model for a prediction
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*/
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/**
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* @typedef List
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* @memberOf! prediction(v1.5)
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* @type object
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* @property {prediction(v1.5).Training[]} items List of models.
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* @property {string} kind What kind of resource this is.
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* @property {string} nextPageToken Pagination token to fetch the next page, if one exists.
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* @property {string} selfLink A URL to re-request this resource.
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*/
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/**
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* @typedef Output
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* @memberOf! prediction(v1.5)
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* @type object
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* @property {string} id The unique name for the predictive model.
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* @property {string} kind What kind of resource this is.
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* @property {string} outputLabel The most likely class label [Categorical models only].
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* @property {object[]} outputMulti A list of class labels with their estimated probabilities [Categorical models only].
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* @property {number} outputValue The estimated regression value [Regression models only].
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* @property {string} selfLink A URL to re-request this resource.
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*/
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/**
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* @typedef Training
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* @memberOf! prediction(v1.5)
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* @type object
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* @property {string} created Insert time of the model (as a RFC 3339 timestamp).
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* @property {string} id The unique name for the predictive model.
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* @property {string} kind What kind of resource this is.
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* @property {object} modelInfo Model metadata.
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* @property {string} modelType Type of predictive model (classification or regression)
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* @property {string} selfLink A URL to re-request this resource.
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* @property {string} storageDataLocation Google storage location of the training data file.
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* @property {string} storagePMMLLocation Google storage location of the preprocessing pmml file.
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* @property {string} storagePMMLModelLocation Google storage location of the pmml model file.
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* @property {string} trainingComplete Training completion time (as a RFC 3339 timestamp).
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* @property {object[]} trainingInstances Instances to train model on.
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* @property {string} trainingStatus The current status of the training job. This can be one of following: RUNNING; DONE; ERROR; ERROR: TRAINING JOB NOT FOUND
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* @property {object[]} utility A class weighting function, which allows the importance weights for class labels to be specified [Categorical models only].
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*/
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/**
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* @typedef Update
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* @memberOf! prediction(v1.5)
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* @type object
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* @property {any[]} csvInstance The input features for this instance
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* @property {string} label The class label of this instance
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* @property {string} output The generic output value - could be regression value or class label
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*/
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export = Prediction;
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