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Unified Diff: generated/googleapis/lib/prediction/v1_6.dart

Issue 3006323002: Api-Roll 54: 2017-09-11 (Closed)
Patch Set: use 2.0.0-dev.infinity sdk constraint in pubspecs Created 3 years, 3 months ago
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Index: generated/googleapis/lib/prediction/v1_6.dart
diff --git a/generated/googleapis/lib/prediction/v1_6.dart b/generated/googleapis/lib/prediction/v1_6.dart
index ffff06fa013cd92df48f1b21c83c8ffb1e0c055a..45da22ec534ad27e01cd551f8510494a33fdad28 100644
--- a/generated/googleapis/lib/prediction/v1_6.dart
+++ b/generated/googleapis/lib/prediction/v1_6.dart
@@ -9,68 +9,71 @@ import 'dart:convert' as convert;
import 'package:_discoveryapis_commons/_discoveryapis_commons.dart' as commons;
import 'package:http/http.dart' as http;
-export 'package:_discoveryapis_commons/_discoveryapis_commons.dart' show
- ApiRequestError, DetailedApiRequestError;
+export 'package:_discoveryapis_commons/_discoveryapis_commons.dart'
+ show ApiRequestError, DetailedApiRequestError;
const core.String USER_AGENT = 'dart-api-client prediction/v1.6';
-/**
- * Lets you access a cloud hosted machine learning service that makes it easy to
- * build smart apps
- */
+/// Lets you access a cloud hosted machine learning service that makes it easy
+/// to build smart apps
class PredictionApi {
- /** View and manage your data across Google Cloud Platform services */
- static const CloudPlatformScope = "https://www.googleapis.com/auth/cloud-platform";
+ /// View and manage your data across Google Cloud Platform services
+ static const CloudPlatformScope =
+ "https://www.googleapis.com/auth/cloud-platform";
- /** Manage your data and permissions in Google Cloud Storage */
- static const DevstorageFullControlScope = "https://www.googleapis.com/auth/devstorage.full_control";
+ /// Manage your data and permissions in Google Cloud Storage
+ static const DevstorageFullControlScope =
+ "https://www.googleapis.com/auth/devstorage.full_control";
- /** View your data in Google Cloud Storage */
- static const DevstorageReadOnlyScope = "https://www.googleapis.com/auth/devstorage.read_only";
+ /// View your data in Google Cloud Storage
+ static const DevstorageReadOnlyScope =
+ "https://www.googleapis.com/auth/devstorage.read_only";
- /** Manage your data in Google Cloud Storage */
- static const DevstorageReadWriteScope = "https://www.googleapis.com/auth/devstorage.read_write";
+ /// Manage your data in Google Cloud Storage
+ static const DevstorageReadWriteScope =
+ "https://www.googleapis.com/auth/devstorage.read_write";
- /** Manage your data in the Google Prediction API */
+ /// Manage your data in the Google Prediction API
static const PredictionScope = "https://www.googleapis.com/auth/prediction";
-
final commons.ApiRequester _requester;
- HostedmodelsResourceApi get hostedmodels => new HostedmodelsResourceApi(_requester);
- TrainedmodelsResourceApi get trainedmodels => new TrainedmodelsResourceApi(_requester);
+ HostedmodelsResourceApi get hostedmodels =>
+ new HostedmodelsResourceApi(_requester);
+ TrainedmodelsResourceApi get trainedmodels =>
+ new TrainedmodelsResourceApi(_requester);
- PredictionApi(http.Client client, {core.String rootUrl: "https://www.googleapis.com/", core.String servicePath: "prediction/v1.6/projects/"}) :
- _requester = new commons.ApiRequester(client, rootUrl, servicePath, USER_AGENT);
+ PredictionApi(http.Client client,
+ {core.String rootUrl: "https://www.googleapis.com/",
+ core.String servicePath: "prediction/v1.6/projects/"})
+ : _requester =
+ new commons.ApiRequester(client, rootUrl, servicePath, USER_AGENT);
}
-
class HostedmodelsResourceApi {
final commons.ApiRequester _requester;
- HostedmodelsResourceApi(commons.ApiRequester client) :
- _requester = client;
-
- /**
- * Submit input and request an output against a hosted model.
- *
- * [request] - The metadata request object.
- *
- * Request parameters:
- *
- * [project] - The project associated with the model.
- *
- * [hostedModelName] - The name of a hosted model.
- *
- * Completes with a [Output].
- *
- * Completes with a [commons.ApiRequestError] if the API endpoint returned an
- * error.
- *
- * If the used [http.Client] completes with an error when making a REST call,
- * this method will complete with the same error.
- */
- async.Future<Output> predict(Input request, core.String project, core.String hostedModelName) {
+ HostedmodelsResourceApi(commons.ApiRequester client) : _requester = client;
+
+ /// Submit input and request an output against a hosted model.
+ ///
+ /// [request] - The metadata request object.
+ ///
+ /// Request parameters:
+ ///
+ /// [project] - The project associated with the model.
+ ///
+ /// [hostedModelName] - The name of a hosted model.
+ ///
+ /// Completes with a [Output].
+ ///
+ /// Completes with a [commons.ApiRequestError] if the API endpoint returned
+ /// an error.
+ ///
+ /// If the used [http.Client] completes with an error when making a REST
+ /// call, this method will complete with the same error.
+ async.Future<Output> predict(
+ Input request, core.String project, core.String hostedModelName) {
var _url = null;
var _queryParams = new core.Map();
var _uploadMedia = null;
@@ -88,44 +91,41 @@ class HostedmodelsResourceApi {
throw new core.ArgumentError("Parameter hostedModelName is required.");
}
- _url = commons.Escaper.ecapeVariable('$project') + '/hostedmodels/' + commons.Escaper.ecapeVariable('$hostedModelName') + '/predict';
+ _url = commons.Escaper.ecapeVariable('$project') +
+ '/hostedmodels/' +
+ commons.Escaper.ecapeVariable('$hostedModelName') +
+ '/predict';
- var _response = _requester.request(_url,
- "POST",
- body: _body,
- queryParams: _queryParams,
- uploadOptions: _uploadOptions,
- uploadMedia: _uploadMedia,
- downloadOptions: _downloadOptions);
+ var _response = _requester.request(_url, "POST",
+ body: _body,
+ queryParams: _queryParams,
+ uploadOptions: _uploadOptions,
+ uploadMedia: _uploadMedia,
+ downloadOptions: _downloadOptions);
return _response.then((data) => new Output.fromJson(data));
}
-
}
-
class TrainedmodelsResourceApi {
final commons.ApiRequester _requester;
- TrainedmodelsResourceApi(commons.ApiRequester client) :
- _requester = client;
-
- /**
- * Get analysis of the model and the data the model was trained on.
- *
- * Request parameters:
- *
- * [project] - The project associated with the model.
- *
- * [id] - The unique name for the predictive model.
- *
- * Completes with a [Analyze].
- *
- * Completes with a [commons.ApiRequestError] if the API endpoint returned an
- * error.
- *
- * If the used [http.Client] completes with an error when making a REST call,
- * this method will complete with the same error.
- */
+ TrainedmodelsResourceApi(commons.ApiRequester client) : _requester = client;
+
+ /// Get analysis of the model and the data the model was trained on.
+ ///
+ /// Request parameters:
+ ///
+ /// [project] - The project associated with the model.
+ ///
+ /// [id] - The unique name for the predictive model.
+ ///
+ /// Completes with a [Analyze].
+ ///
+ /// Completes with a [commons.ApiRequestError] if the API endpoint returned
+ /// an error.
+ ///
+ /// If the used [http.Client] completes with an error when making a REST
+ /// call, this method will complete with the same error.
async.Future<Analyze> analyze(core.String project, core.String id) {
var _url = null;
var _queryParams = new core.Map();
@@ -141,33 +141,33 @@ class TrainedmodelsResourceApi {
throw new core.ArgumentError("Parameter id is required.");
}
- _url = commons.Escaper.ecapeVariable('$project') + '/trainedmodels/' + commons.Escaper.ecapeVariable('$id') + '/analyze';
+ _url = commons.Escaper.ecapeVariable('$project') +
+ '/trainedmodels/' +
+ commons.Escaper.ecapeVariable('$id') +
+ '/analyze';
- var _response = _requester.request(_url,
- "GET",
- body: _body,
- queryParams: _queryParams,
- uploadOptions: _uploadOptions,
- uploadMedia: _uploadMedia,
- downloadOptions: _downloadOptions);
+ var _response = _requester.request(_url, "GET",
+ body: _body,
+ queryParams: _queryParams,
+ uploadOptions: _uploadOptions,
+ uploadMedia: _uploadMedia,
+ downloadOptions: _downloadOptions);
return _response.then((data) => new Analyze.fromJson(data));
}
- /**
- * Delete a trained model.
- *
- * Request parameters:
- *
- * [project] - The project associated with the model.
- *
- * [id] - The unique name for the predictive model.
- *
- * Completes with a [commons.ApiRequestError] if the API endpoint returned an
- * error.
- *
- * If the used [http.Client] completes with an error when making a REST call,
- * this method will complete with the same error.
- */
+ /// Delete a trained model.
+ ///
+ /// Request parameters:
+ ///
+ /// [project] - The project associated with the model.
+ ///
+ /// [id] - The unique name for the predictive model.
+ ///
+ /// Completes with a [commons.ApiRequestError] if the API endpoint returned
+ /// an error.
+ ///
+ /// If the used [http.Client] completes with an error when making a REST
+ /// call, this method will complete with the same error.
async.Future delete(core.String project, core.String id) {
var _url = null;
var _queryParams = new core.Map();
@@ -185,35 +185,34 @@ class TrainedmodelsResourceApi {
_downloadOptions = null;
- _url = commons.Escaper.ecapeVariable('$project') + '/trainedmodels/' + commons.Escaper.ecapeVariable('$id');
+ _url = commons.Escaper.ecapeVariable('$project') +
+ '/trainedmodels/' +
+ commons.Escaper.ecapeVariable('$id');
- var _response = _requester.request(_url,
- "DELETE",
- body: _body,
- queryParams: _queryParams,
- uploadOptions: _uploadOptions,
- uploadMedia: _uploadMedia,
- downloadOptions: _downloadOptions);
+ var _response = _requester.request(_url, "DELETE",
+ body: _body,
+ queryParams: _queryParams,
+ uploadOptions: _uploadOptions,
+ uploadMedia: _uploadMedia,
+ downloadOptions: _downloadOptions);
return _response.then((data) => null);
}
- /**
- * Check training status of your model.
- *
- * Request parameters:
- *
- * [project] - The project associated with the model.
- *
- * [id] - The unique name for the predictive model.
- *
- * Completes with a [Insert2].
- *
- * Completes with a [commons.ApiRequestError] if the API endpoint returned an
- * error.
- *
- * If the used [http.Client] completes with an error when making a REST call,
- * this method will complete with the same error.
- */
+ /// Check training status of your model.
+ ///
+ /// Request parameters:
+ ///
+ /// [project] - The project associated with the model.
+ ///
+ /// [id] - The unique name for the predictive model.
+ ///
+ /// Completes with a [Insert2].
+ ///
+ /// Completes with a [commons.ApiRequestError] if the API endpoint returned
+ /// an error.
+ ///
+ /// If the used [http.Client] completes with an error when making a REST
+ /// call, this method will complete with the same error.
async.Future<Insert2> get(core.String project, core.String id) {
var _url = null;
var _queryParams = new core.Map();
@@ -229,35 +228,34 @@ class TrainedmodelsResourceApi {
throw new core.ArgumentError("Parameter id is required.");
}
- _url = commons.Escaper.ecapeVariable('$project') + '/trainedmodels/' + commons.Escaper.ecapeVariable('$id');
+ _url = commons.Escaper.ecapeVariable('$project') +
+ '/trainedmodels/' +
+ commons.Escaper.ecapeVariable('$id');
- var _response = _requester.request(_url,
- "GET",
- body: _body,
- queryParams: _queryParams,
- uploadOptions: _uploadOptions,
- uploadMedia: _uploadMedia,
- downloadOptions: _downloadOptions);
+ var _response = _requester.request(_url, "GET",
+ body: _body,
+ queryParams: _queryParams,
+ uploadOptions: _uploadOptions,
+ uploadMedia: _uploadMedia,
+ downloadOptions: _downloadOptions);
return _response.then((data) => new Insert2.fromJson(data));
}
- /**
- * Train a Prediction API model.
- *
- * [request] - The metadata request object.
- *
- * Request parameters:
- *
- * [project] - The project associated with the model.
- *
- * Completes with a [Insert2].
- *
- * Completes with a [commons.ApiRequestError] if the API endpoint returned an
- * error.
- *
- * If the used [http.Client] completes with an error when making a REST call,
- * this method will complete with the same error.
- */
+ /// Train a Prediction API model.
+ ///
+ /// [request] - The metadata request object.
+ ///
+ /// Request parameters:
+ ///
+ /// [project] - The project associated with the model.
+ ///
+ /// Completes with a [Insert2].
+ ///
+ /// Completes with a [commons.ApiRequestError] if the API endpoint returned
+ /// an error.
+ ///
+ /// If the used [http.Client] completes with an error when making a REST
+ /// call, this method will complete with the same error.
async.Future<Insert2> insert(Insert request, core.String project) {
var _url = null;
var _queryParams = new core.Map();
@@ -275,36 +273,34 @@ class TrainedmodelsResourceApi {
_url = commons.Escaper.ecapeVariable('$project') + '/trainedmodels';
- var _response = _requester.request(_url,
- "POST",
- body: _body,
- queryParams: _queryParams,
- uploadOptions: _uploadOptions,
- uploadMedia: _uploadMedia,
- downloadOptions: _downloadOptions);
+ var _response = _requester.request(_url, "POST",
+ body: _body,
+ queryParams: _queryParams,
+ uploadOptions: _uploadOptions,
+ uploadMedia: _uploadMedia,
+ downloadOptions: _downloadOptions);
return _response.then((data) => new Insert2.fromJson(data));
}
- /**
- * List available models.
- *
- * Request parameters:
- *
- * [project] - The project associated with the model.
- *
- * [maxResults] - Maximum number of results to return.
- *
- * [pageToken] - Pagination token.
- *
- * Completes with a [List].
- *
- * Completes with a [commons.ApiRequestError] if the API endpoint returned an
- * error.
- *
- * If the used [http.Client] completes with an error when making a REST call,
- * this method will complete with the same error.
- */
- async.Future<List> list(core.String project, {core.int maxResults, core.String pageToken}) {
+ /// List available models.
+ ///
+ /// Request parameters:
+ ///
+ /// [project] - The project associated with the model.
+ ///
+ /// [maxResults] - Maximum number of results to return.
+ ///
+ /// [pageToken] - Pagination token.
+ ///
+ /// Completes with a [List].
+ ///
+ /// Completes with a [commons.ApiRequestError] if the API endpoint returned
+ /// an error.
+ ///
+ /// If the used [http.Client] completes with an error when making a REST
+ /// call, this method will complete with the same error.
+ async.Future<List> list(core.String project,
+ {core.int maxResults, core.String pageToken}) {
var _url = null;
var _queryParams = new core.Map();
var _uploadMedia = null;
@@ -324,36 +320,34 @@ class TrainedmodelsResourceApi {
_url = commons.Escaper.ecapeVariable('$project') + '/trainedmodels/list';
- var _response = _requester.request(_url,
- "GET",
- body: _body,
- queryParams: _queryParams,
- uploadOptions: _uploadOptions,
- uploadMedia: _uploadMedia,
- downloadOptions: _downloadOptions);
+ var _response = _requester.request(_url, "GET",
+ body: _body,
+ queryParams: _queryParams,
+ uploadOptions: _uploadOptions,
+ uploadMedia: _uploadMedia,
+ downloadOptions: _downloadOptions);
return _response.then((data) => new List.fromJson(data));
}
- /**
- * Submit model id and request a prediction.
- *
- * [request] - The metadata request object.
- *
- * Request parameters:
- *
- * [project] - The project associated with the model.
- *
- * [id] - The unique name for the predictive model.
- *
- * Completes with a [Output].
- *
- * Completes with a [commons.ApiRequestError] if the API endpoint returned an
- * error.
- *
- * If the used [http.Client] completes with an error when making a REST call,
- * this method will complete with the same error.
- */
- async.Future<Output> predict(Input request, core.String project, core.String id) {
+ /// Submit model id and request a prediction.
+ ///
+ /// [request] - The metadata request object.
+ ///
+ /// Request parameters:
+ ///
+ /// [project] - The project associated with the model.
+ ///
+ /// [id] - The unique name for the predictive model.
+ ///
+ /// Completes with a [Output].
+ ///
+ /// Completes with a [commons.ApiRequestError] if the API endpoint returned
+ /// an error.
+ ///
+ /// If the used [http.Client] completes with an error when making a REST
+ /// call, this method will complete with the same error.
+ async.Future<Output> predict(
+ Input request, core.String project, core.String id) {
var _url = null;
var _queryParams = new core.Map();
var _uploadMedia = null;
@@ -371,38 +365,39 @@ class TrainedmodelsResourceApi {
throw new core.ArgumentError("Parameter id is required.");
}
- _url = commons.Escaper.ecapeVariable('$project') + '/trainedmodels/' + commons.Escaper.ecapeVariable('$id') + '/predict';
+ _url = commons.Escaper.ecapeVariable('$project') +
+ '/trainedmodels/' +
+ commons.Escaper.ecapeVariable('$id') +
+ '/predict';
- var _response = _requester.request(_url,
- "POST",
- body: _body,
- queryParams: _queryParams,
- uploadOptions: _uploadOptions,
- uploadMedia: _uploadMedia,
- downloadOptions: _downloadOptions);
+ var _response = _requester.request(_url, "POST",
+ body: _body,
+ queryParams: _queryParams,
+ uploadOptions: _uploadOptions,
+ uploadMedia: _uploadMedia,
+ downloadOptions: _downloadOptions);
return _response.then((data) => new Output.fromJson(data));
}
- /**
- * Add new data to a trained model.
- *
- * [request] - The metadata request object.
- *
- * Request parameters:
- *
- * [project] - The project associated with the model.
- *
- * [id] - The unique name for the predictive model.
- *
- * Completes with a [Insert2].
- *
- * Completes with a [commons.ApiRequestError] if the API endpoint returned an
- * error.
- *
- * If the used [http.Client] completes with an error when making a REST call,
- * this method will complete with the same error.
- */
- async.Future<Insert2> update(Update request, core.String project, core.String id) {
+ /// Add new data to a trained model.
+ ///
+ /// [request] - The metadata request object.
+ ///
+ /// Request parameters:
+ ///
+ /// [project] - The project associated with the model.
+ ///
+ /// [id] - The unique name for the predictive model.
+ ///
+ /// Completes with a [Insert2].
+ ///
+ /// Completes with a [commons.ApiRequestError] if the API endpoint returned
+ /// an error.
+ ///
+ /// If the used [http.Client] completes with an error when making a REST
+ /// call, this method will complete with the same error.
+ async.Future<Insert2> update(
+ Update request, core.String project, core.String id) {
var _url = null;
var _queryParams = new core.Map();
var _uploadMedia = null;
@@ -420,26 +415,25 @@ class TrainedmodelsResourceApi {
throw new core.ArgumentError("Parameter id is required.");
}
- _url = commons.Escaper.ecapeVariable('$project') + '/trainedmodels/' + commons.Escaper.ecapeVariable('$id');
+ _url = commons.Escaper.ecapeVariable('$project') +
+ '/trainedmodels/' +
+ commons.Escaper.ecapeVariable('$id');
- var _response = _requester.request(_url,
- "PUT",
- body: _body,
- queryParams: _queryParams,
- uploadOptions: _uploadOptions,
- uploadMedia: _uploadMedia,
- downloadOptions: _downloadOptions);
+ var _response = _requester.request(_url, "PUT",
+ body: _body,
+ queryParams: _queryParams,
+ uploadOptions: _uploadOptions,
+ uploadMedia: _uploadMedia,
+ downloadOptions: _downloadOptions);
return _response.then((data) => new Insert2.fromJson(data));
}
-
}
-
-
class AnalyzeDataDescriptionFeaturesCategoricalValues {
- /** Number of times this feature had this value. */
+ /// Number of times this feature had this value.
core.String count;
- /** The category name. */
+
+ /// The category name.
core.String value;
AnalyzeDataDescriptionFeaturesCategoricalValues();
@@ -454,7 +448,8 @@ class AnalyzeDataDescriptionFeaturesCategoricalValues {
}
core.Map<core.String, core.Object> toJson() {
- final core.Map<core.String, core.Object> _json = new core.Map<core.String, core.Object>();
+ final core.Map<core.String, core.Object> _json =
+ new core.Map<core.String, core.Object>();
if (count != null) {
_json["count"] = count;
}
@@ -465,11 +460,12 @@ class AnalyzeDataDescriptionFeaturesCategoricalValues {
}
}
-/** Description of the categorical values of this feature. */
+/// Description of the categorical values of this feature.
class AnalyzeDataDescriptionFeaturesCategorical {
- /** Number of categorical values for this feature in the data. */
+ /// Number of categorical values for this feature in the data.
core.String count;
- /** List of all the categories for this feature in the data set. */
+
+ /// List of all the categories for this feature in the data set.
core.List<AnalyzeDataDescriptionFeaturesCategoricalValues> values;
AnalyzeDataDescriptionFeaturesCategorical();
@@ -479,12 +475,17 @@ class AnalyzeDataDescriptionFeaturesCategorical {
count = _json["count"];
}
if (_json.containsKey("values")) {
- values = _json["values"].map((value) => new AnalyzeDataDescriptionFeaturesCategoricalValues.fromJson(value)).toList();
+ values = _json["values"]
+ .map((value) =>
+ new AnalyzeDataDescriptionFeaturesCategoricalValues.fromJson(
+ value))
+ .toList();
}
}
core.Map<core.String, core.Object> toJson() {
- final core.Map<core.String, core.Object> _json = new core.Map<core.String, core.Object>();
+ final core.Map<core.String, core.Object> _json =
+ new core.Map<core.String, core.Object>();
if (count != null) {
_json["count"] = count;
}
@@ -495,13 +496,15 @@ class AnalyzeDataDescriptionFeaturesCategorical {
}
}
-/** Description of the numeric values of this feature. */
+/// Description of the numeric values of this feature.
class AnalyzeDataDescriptionFeaturesNumeric {
- /** Number of numeric values for this feature in the data set. */
+ /// Number of numeric values for this feature in the data set.
core.String count;
- /** Mean of the numeric values of this feature in the data set. */
+
+ /// Mean of the numeric values of this feature in the data set.
core.String mean;
- /** Variance of the numeric values of this feature in the data set. */
+
+ /// Variance of the numeric values of this feature in the data set.
core.String variance;
AnalyzeDataDescriptionFeaturesNumeric();
@@ -519,7 +522,8 @@ class AnalyzeDataDescriptionFeaturesNumeric {
}
core.Map<core.String, core.Object> toJson() {
- final core.Map<core.String, core.Object> _json = new core.Map<core.String, core.Object>();
+ final core.Map<core.String, core.Object> _json =
+ new core.Map<core.String, core.Object>();
if (count != null) {
_json["count"] = count;
}
@@ -533,9 +537,9 @@ class AnalyzeDataDescriptionFeaturesNumeric {
}
}
-/** Description of multiple-word text values of this feature. */
+/// Description of multiple-word text values of this feature.
class AnalyzeDataDescriptionFeaturesText {
- /** Number of multiple-word text values for this feature. */
+ /// Number of multiple-word text values for this feature.
core.String count;
AnalyzeDataDescriptionFeaturesText();
@@ -547,7 +551,8 @@ class AnalyzeDataDescriptionFeaturesText {
}
core.Map<core.String, core.Object> toJson() {
- final core.Map<core.String, core.Object> _json = new core.Map<core.String, core.Object>();
+ final core.Map<core.String, core.Object> _json =
+ new core.Map<core.String, core.Object>();
if (count != null) {
_json["count"] = count;
}
@@ -556,26 +561,31 @@ class AnalyzeDataDescriptionFeaturesText {
}
class AnalyzeDataDescriptionFeatures {
- /** Description of the categorical values of this feature. */
+ /// Description of the categorical values of this feature.
AnalyzeDataDescriptionFeaturesCategorical categorical;
- /** The feature index. */
+
+ /// The feature index.
core.String index;
- /** Description of the numeric values of this feature. */
+
+ /// Description of the numeric values of this feature.
AnalyzeDataDescriptionFeaturesNumeric numeric;
- /** Description of multiple-word text values of this feature. */
+
+ /// Description of multiple-word text values of this feature.
AnalyzeDataDescriptionFeaturesText text;
AnalyzeDataDescriptionFeatures();
AnalyzeDataDescriptionFeatures.fromJson(core.Map _json) {
if (_json.containsKey("categorical")) {
- categorical = new AnalyzeDataDescriptionFeaturesCategorical.fromJson(_json["categorical"]);
+ categorical = new AnalyzeDataDescriptionFeaturesCategorical.fromJson(
+ _json["categorical"]);
}
if (_json.containsKey("index")) {
index = _json["index"];
}
if (_json.containsKey("numeric")) {
- numeric = new AnalyzeDataDescriptionFeaturesNumeric.fromJson(_json["numeric"]);
+ numeric =
+ new AnalyzeDataDescriptionFeaturesNumeric.fromJson(_json["numeric"]);
}
if (_json.containsKey("text")) {
text = new AnalyzeDataDescriptionFeaturesText.fromJson(_json["text"]);
@@ -583,7 +593,8 @@ class AnalyzeDataDescriptionFeatures {
}
core.Map<core.String, core.Object> toJson() {
- final core.Map<core.String, core.Object> _json = new core.Map<core.String, core.Object>();
+ final core.Map<core.String, core.Object> _json =
+ new core.Map<core.String, core.Object>();
if (categorical != null) {
_json["categorical"] = (categorical).toJson();
}
@@ -600,13 +611,15 @@ class AnalyzeDataDescriptionFeatures {
}
}
-/** Description of the output values in the data set. */
+/// Description of the output values in the data set.
class AnalyzeDataDescriptionOutputFeatureNumeric {
- /** Number of numeric output values in the data set. */
+ /// Number of numeric output values in the data set.
core.String count;
- /** Mean of the output values in the data set. */
+
+ /// Mean of the output values in the data set.
core.String mean;
- /** Variance of the output values in the data set. */
+
+ /// Variance of the output values in the data set.
core.String variance;
AnalyzeDataDescriptionOutputFeatureNumeric();
@@ -624,7 +637,8 @@ class AnalyzeDataDescriptionOutputFeatureNumeric {
}
core.Map<core.String, core.Object> toJson() {
- final core.Map<core.String, core.Object> _json = new core.Map<core.String, core.Object>();
+ final core.Map<core.String, core.Object> _json =
+ new core.Map<core.String, core.Object>();
if (count != null) {
_json["count"] = count;
}
@@ -639,9 +653,10 @@ class AnalyzeDataDescriptionOutputFeatureNumeric {
}
class AnalyzeDataDescriptionOutputFeatureText {
- /** Number of times the output label occurred in the data set. */
+ /// Number of times the output label occurred in the data set.
core.String count;
- /** The output label. */
+
+ /// The output label.
core.String value;
AnalyzeDataDescriptionOutputFeatureText();
@@ -656,7 +671,8 @@ class AnalyzeDataDescriptionOutputFeatureText {
}
core.Map<core.String, core.Object> toJson() {
- final core.Map<core.String, core.Object> _json = new core.Map<core.String, core.Object>();
+ final core.Map<core.String, core.Object> _json =
+ new core.Map<core.String, core.Object>();
if (count != null) {
_json["count"] = count;
}
@@ -667,26 +683,32 @@ class AnalyzeDataDescriptionOutputFeatureText {
}
}
-/** Description of the output value or label. */
+/// Description of the output value or label.
class AnalyzeDataDescriptionOutputFeature {
- /** Description of the output values in the data set. */
+ /// Description of the output values in the data set.
AnalyzeDataDescriptionOutputFeatureNumeric numeric;
- /** Description of the output labels in the data set. */
+
+ /// Description of the output labels in the data set.
core.List<AnalyzeDataDescriptionOutputFeatureText> text;
AnalyzeDataDescriptionOutputFeature();
AnalyzeDataDescriptionOutputFeature.fromJson(core.Map _json) {
if (_json.containsKey("numeric")) {
- numeric = new AnalyzeDataDescriptionOutputFeatureNumeric.fromJson(_json["numeric"]);
+ numeric = new AnalyzeDataDescriptionOutputFeatureNumeric.fromJson(
+ _json["numeric"]);
}
if (_json.containsKey("text")) {
- text = _json["text"].map((value) => new AnalyzeDataDescriptionOutputFeatureText.fromJson(value)).toList();
+ text = _json["text"]
+ .map((value) =>
+ new AnalyzeDataDescriptionOutputFeatureText.fromJson(value))
+ .toList();
}
}
core.Map<core.String, core.Object> toJson() {
- final core.Map<core.String, core.Object> _json = new core.Map<core.String, core.Object>();
+ final core.Map<core.String, core.Object> _json =
+ new core.Map<core.String, core.Object>();
if (numeric != null) {
_json["numeric"] = (numeric).toJson();
}
@@ -697,26 +719,31 @@ class AnalyzeDataDescriptionOutputFeature {
}
}
-/** Description of the data the model was trained on. */
+/// Description of the data the model was trained on.
class AnalyzeDataDescription {
- /** Description of the input features in the data set. */
+ /// Description of the input features in the data set.
core.List<AnalyzeDataDescriptionFeatures> features;
- /** Description of the output value or label. */
+
+ /// Description of the output value or label.
AnalyzeDataDescriptionOutputFeature outputFeature;
AnalyzeDataDescription();
AnalyzeDataDescription.fromJson(core.Map _json) {
if (_json.containsKey("features")) {
- features = _json["features"].map((value) => new AnalyzeDataDescriptionFeatures.fromJson(value)).toList();
+ features = _json["features"]
+ .map((value) => new AnalyzeDataDescriptionFeatures.fromJson(value))
+ .toList();
}
if (_json.containsKey("outputFeature")) {
- outputFeature = new AnalyzeDataDescriptionOutputFeature.fromJson(_json["outputFeature"]);
+ outputFeature = new AnalyzeDataDescriptionOutputFeature.fromJson(
+ _json["outputFeature"]);
}
}
core.Map<core.String, core.Object> toJson() {
- final core.Map<core.String, core.Object> _json = new core.Map<core.String, core.Object>();
+ final core.Map<core.String, core.Object> _json =
+ new core.Map<core.String, core.Object>();
if (features != null) {
_json["features"] = features.map((value) => (value).toJson()).toList();
}
@@ -727,20 +754,20 @@ class AnalyzeDataDescription {
}
}
-/** Description of the model. */
+/// Description of the model.
class AnalyzeModelDescription {
- /**
- * An output confusion matrix. This shows an estimate for how this model will
- * do in predictions. This is first indexed by the true class label. For each
- * true class label, this provides a pair {predicted_label, count}, where
- * count is the estimated number of times the model will predict the predicted
- * label given the true label. Will not output if more then 100 classes
- * (Categorical models only).
- */
+ /// An output confusion matrix. This shows an estimate for how this model
+ /// will do in predictions. This is first indexed by the true class label.
+ /// For each true class label, this provides a pair {predicted_label, count},
+ /// where count is the estimated number of times the model will predict the
+ /// predicted label given the true label. Will not output if more then 100
+ /// classes (Categorical models only).
core.Map<core.String, core.Map<core.String, core.String>> confusionMatrix;
- /** A list of the confusion matrix row totals. */
+
+ /// A list of the confusion matrix row totals.
core.Map<core.String, core.String> confusionMatrixRowTotals;
- /** Basic information about the model. */
+
+ /// Basic information about the model.
Insert2 modelinfo;
AnalyzeModelDescription();
@@ -758,7 +785,8 @@ class AnalyzeModelDescription {
}
core.Map<core.String, core.Object> toJson() {
- final core.Map<core.String, core.Object> _json = new core.Map<core.String, core.Object>();
+ final core.Map<core.String, core.Object> _json =
+ new core.Map<core.String, core.Object>();
if (confusionMatrix != null) {
_json["confusionMatrix"] = confusionMatrix;
}
@@ -773,24 +801,30 @@ class AnalyzeModelDescription {
}
class Analyze {
- /** Description of the data the model was trained on. */
+ /// Description of the data the model was trained on.
AnalyzeDataDescription dataDescription;
- /** List of errors with the data. */
+
+ /// List of errors with the data.
core.List<core.Map<core.String, core.String>> errors;
- /** The unique name for the predictive model. */
+
+ /// The unique name for the predictive model.
core.String id;
- /** What kind of resource this is. */
+
+ /// What kind of resource this is.
core.String kind;
- /** Description of the model. */
+
+ /// Description of the model.
AnalyzeModelDescription modelDescription;
- /** A URL to re-request this resource. */
+
+ /// A URL to re-request this resource.
core.String selfLink;
Analyze();
Analyze.fromJson(core.Map _json) {
if (_json.containsKey("dataDescription")) {
- dataDescription = new AnalyzeDataDescription.fromJson(_json["dataDescription"]);
+ dataDescription =
+ new AnalyzeDataDescription.fromJson(_json["dataDescription"]);
}
if (_json.containsKey("errors")) {
errors = _json["errors"];
@@ -802,7 +836,8 @@ class Analyze {
kind = _json["kind"];
}
if (_json.containsKey("modelDescription")) {
- modelDescription = new AnalyzeModelDescription.fromJson(_json["modelDescription"]);
+ modelDescription =
+ new AnalyzeModelDescription.fromJson(_json["modelDescription"]);
}
if (_json.containsKey("selfLink")) {
selfLink = _json["selfLink"];
@@ -810,7 +845,8 @@ class Analyze {
}
core.Map<core.String, core.Object> toJson() {
- final core.Map<core.String, core.Object> _json = new core.Map<core.String, core.Object>();
+ final core.Map<core.String, core.Object> _json =
+ new core.Map<core.String, core.Object>();
if (dataDescription != null) {
_json["dataDescription"] = (dataDescription).toJson();
}
@@ -833,14 +869,12 @@ class Analyze {
}
}
-/** Input to the model for a prediction. */
+/// Input to the model for a prediction.
class InputInput {
- /**
- * A list of input features, these can be strings or doubles.
- *
- * The values for Object must be JSON objects. It can consist of `num`,
- * `String`, `bool` and `null` as well as `Map` and `List` values.
- */
+ /// A list of input features, these can be strings or doubles.
+ ///
+ /// The values for Object must be JSON objects. It can consist of `num`,
+ /// `String`, `bool` and `null` as well as `Map` and `List` values.
core.List<core.Object> csvInstance;
InputInput();
@@ -852,7 +886,8 @@ class InputInput {
}
core.Map<core.String, core.Object> toJson() {
- final core.Map<core.String, core.Object> _json = new core.Map<core.String, core.Object>();
+ final core.Map<core.String, core.Object> _json =
+ new core.Map<core.String, core.Object>();
if (csvInstance != null) {
_json["csvInstance"] = csvInstance;
}
@@ -861,7 +896,7 @@ class InputInput {
}
class Input {
- /** Input to the model for a prediction. */
+ /// Input to the model for a prediction.
InputInput input;
Input();
@@ -873,7 +908,8 @@ class Input {
}
core.Map<core.String, core.Object> toJson() {
- final core.Map<core.String, core.Object> _json = new core.Map<core.String, core.Object>();
+ final core.Map<core.String, core.Object> _json =
+ new core.Map<core.String, core.Object>();
if (input != null) {
_json["input"] = (input).toJson();
}
@@ -882,14 +918,13 @@ class Input {
}
class InsertTrainingInstances {
- /**
- * The input features for this instance.
- *
- * The values for Object must be JSON objects. It can consist of `num`,
- * `String`, `bool` and `null` as well as `Map` and `List` values.
- */
+ /// The input features for this instance.
+ ///
+ /// The values for Object must be JSON objects. It can consist of `num`,
+ /// `String`, `bool` and `null` as well as `Map` and `List` values.
core.List<core.Object> csvInstance;
- /** The generic output value - could be regression or class label. */
+
+ /// The generic output value - could be regression or class label.
core.String output;
InsertTrainingInstances();
@@ -904,7 +939,8 @@ class InsertTrainingInstances {
}
core.Map<core.String, core.Object> toJson() {
- final core.Map<core.String, core.Object> _json = new core.Map<core.String, core.Object>();
+ final core.Map<core.String, core.Object> _json =
+ new core.Map<core.String, core.Object>();
if (csvInstance != null) {
_json["csvInstance"] = csvInstance;
}
@@ -916,24 +952,29 @@ class InsertTrainingInstances {
}
class Insert {
- /** The unique name for the predictive model. */
+ /// The unique name for the predictive model.
core.String id;
- /** Type of predictive model (classification or regression). */
+
+ /// Type of predictive model (classification or regression).
core.String modelType;
- /** The Id of the model to be copied over. */
+
+ /// The Id of the model to be copied over.
core.String sourceModel;
- /** Google storage location of the training data file. */
+
+ /// Google storage location of the training data file.
core.String storageDataLocation;
- /** Google storage location of the preprocessing pmml file. */
+
+ /// Google storage location of the preprocessing pmml file.
core.String storagePMMLLocation;
- /** Google storage location of the pmml model file. */
+
+ /// Google storage location of the pmml model file.
core.String storagePMMLModelLocation;
- /** Instances to train model on. */
+
+ /// Instances to train model on.
core.List<InsertTrainingInstances> trainingInstances;
- /**
- * A class weighting function, which allows the importance weights for class
- * labels to be specified (Categorical models only).
- */
+
+ /// A class weighting function, which allows the importance weights for class
+ /// labels to be specified (Categorical models only).
core.List<core.Map<core.String, core.double>> utility;
Insert();
@@ -958,7 +999,9 @@ class Insert {
storagePMMLModelLocation = _json["storagePMMLModelLocation"];
}
if (_json.containsKey("trainingInstances")) {
- trainingInstances = _json["trainingInstances"].map((value) => new InsertTrainingInstances.fromJson(value)).toList();
+ trainingInstances = _json["trainingInstances"]
+ .map((value) => new InsertTrainingInstances.fromJson(value))
+ .toList();
}
if (_json.containsKey("utility")) {
utility = _json["utility"];
@@ -966,7 +1009,8 @@ class Insert {
}
core.Map<core.String, core.Object> toJson() {
- final core.Map<core.String, core.Object> _json = new core.Map<core.String, core.Object>();
+ final core.Map<core.String, core.Object> _json =
+ new core.Map<core.String, core.Object>();
if (id != null) {
_json["id"] = id;
}
@@ -986,7 +1030,8 @@ class Insert {
_json["storagePMMLModelLocation"] = storagePMMLModelLocation;
}
if (trainingInstances != null) {
- _json["trainingInstances"] = trainingInstances.map((value) => (value).toJson()).toList();
+ _json["trainingInstances"] =
+ trainingInstances.map((value) => (value).toJson()).toList();
}
if (utility != null) {
_json["utility"] = utility;
@@ -995,32 +1040,31 @@ class Insert {
}
}
-/** Model metadata. */
+/// Model metadata.
class Insert2ModelInfo {
- /**
- * Estimated accuracy of model taking utility weights into account
- * (Categorical models only).
- */
+ /// Estimated accuracy of model taking utility weights into account
+ /// (Categorical models only).
core.String classWeightedAccuracy;
- /**
- * A number between 0.0 and 1.0, where 1.0 is 100% accurate. This is an
- * estimate, based on the amount and quality of the training data, of the
- * estimated prediction accuracy. You can use this is a guide to decide
- * whether the results are accurate enough for your needs. This estimate will
- * be more reliable if your real input data is similar to your training data
- * (Categorical models only).
- */
+
+ /// A number between 0.0 and 1.0, where 1.0 is 100% accurate. This is an
+ /// estimate, based on the amount and quality of the training data, of the
+ /// estimated prediction accuracy. You can use this is a guide to decide
+ /// whether the results are accurate enough for your needs. This estimate
+ /// will be more reliable if your real input data is similar to your training
+ /// data (Categorical models only).
core.String classificationAccuracy;
- /**
- * An estimated mean squared error. The can be used to measure the quality of
- * the predicted model (Regression models only).
- */
+
+ /// An estimated mean squared error. The can be used to measure the quality
+ /// of the predicted model (Regression models only).
core.String meanSquaredError;
- /** Type of predictive model (CLASSIFICATION or REGRESSION). */
+
+ /// Type of predictive model (CLASSIFICATION or REGRESSION).
core.String modelType;
- /** Number of valid data instances used in the trained model. */
+
+ /// Number of valid data instances used in the trained model.
core.String numberInstances;
- /** Number of class labels in the trained model (Categorical models only). */
+
+ /// Number of class labels in the trained model (Categorical models only).
core.String numberLabels;
Insert2ModelInfo();
@@ -1047,7 +1091,8 @@ class Insert2ModelInfo {
}
core.Map<core.String, core.Object> toJson() {
- final core.Map<core.String, core.Object> _json = new core.Map<core.String, core.Object>();
+ final core.Map<core.String, core.Object> _json =
+ new core.Map<core.String, core.Object>();
if (classWeightedAccuracy != null) {
_json["classWeightedAccuracy"] = classWeightedAccuracy;
}
@@ -1071,30 +1116,38 @@ class Insert2ModelInfo {
}
class Insert2 {
- /** Insert time of the model (as a RFC 3339 timestamp). */
+ /// Insert time of the model (as a RFC 3339 timestamp).
core.DateTime created;
- /** The unique name for the predictive model. */
+
+ /// The unique name for the predictive model.
core.String id;
- /** What kind of resource this is. */
+
+ /// What kind of resource this is.
core.String kind;
- /** Model metadata. */
+
+ /// Model metadata.
Insert2ModelInfo modelInfo;
- /** Type of predictive model (CLASSIFICATION or REGRESSION). */
+
+ /// Type of predictive model (CLASSIFICATION or REGRESSION).
core.String modelType;
- /** A URL to re-request this resource. */
+
+ /// A URL to re-request this resource.
core.String selfLink;
- /** Google storage location of the training data file. */
+
+ /// Google storage location of the training data file.
core.String storageDataLocation;
- /** Google storage location of the preprocessing pmml file. */
+
+ /// Google storage location of the preprocessing pmml file.
core.String storagePMMLLocation;
- /** Google storage location of the pmml model file. */
+
+ /// Google storage location of the pmml model file.
core.String storagePMMLModelLocation;
- /** Training completion time (as a RFC 3339 timestamp). */
+
+ /// Training completion time (as a RFC 3339 timestamp).
core.DateTime trainingComplete;
- /**
- * The current status of the training job. This can be one of following:
- * RUNNING; DONE; ERROR; ERROR: TRAINING JOB NOT FOUND
- */
+
+ /// The current status of the training job. This can be one of following:
+ /// RUNNING; DONE; ERROR; ERROR: TRAINING JOB NOT FOUND
core.String trainingStatus;
Insert2();
@@ -1136,7 +1189,8 @@ class Insert2 {
}
core.Map<core.String, core.Object> toJson() {
- final core.Map<core.String, core.Object> _json = new core.Map<core.String, core.Object>();
+ final core.Map<core.String, core.Object> _json =
+ new core.Map<core.String, core.Object>();
if (created != null) {
_json["created"] = (created).toIso8601String();
}
@@ -1175,20 +1229,24 @@ class Insert2 {
}
class List {
- /** List of models. */
+ /// List of models.
core.List<Insert2> items;
- /** What kind of resource this is. */
+
+ /// What kind of resource this is.
core.String kind;
- /** Pagination token to fetch the next page, if one exists. */
+
+ /// Pagination token to fetch the next page, if one exists.
core.String nextPageToken;
- /** A URL to re-request this resource. */
+
+ /// A URL to re-request this resource.
core.String selfLink;
List();
List.fromJson(core.Map _json) {
if (_json.containsKey("items")) {
- items = _json["items"].map((value) => new Insert2.fromJson(value)).toList();
+ items =
+ _json["items"].map((value) => new Insert2.fromJson(value)).toList();
}
if (_json.containsKey("kind")) {
kind = _json["kind"];
@@ -1202,7 +1260,8 @@ class List {
}
core.Map<core.String, core.Object> toJson() {
- final core.Map<core.String, core.Object> _json = new core.Map<core.String, core.Object>();
+ final core.Map<core.String, core.Object> _json =
+ new core.Map<core.String, core.Object>();
if (items != null) {
_json["items"] = items.map((value) => (value).toJson()).toList();
}
@@ -1220,9 +1279,10 @@ class List {
}
class OutputOutputMulti {
- /** The class label. */
+ /// The class label.
core.String label;
- /** The probability of the class label. */
+
+ /// The probability of the class label.
core.String score;
OutputOutputMulti();
@@ -1237,7 +1297,8 @@ class OutputOutputMulti {
}
core.Map<core.String, core.Object> toJson() {
- final core.Map<core.String, core.Object> _json = new core.Map<core.String, core.Object>();
+ final core.Map<core.String, core.Object> _json =
+ new core.Map<core.String, core.Object>();
if (label != null) {
_json["label"] = label;
}
@@ -1249,20 +1310,23 @@ class OutputOutputMulti {
}
class Output {
- /** The unique name for the predictive model. */
+ /// The unique name for the predictive model.
core.String id;
- /** What kind of resource this is. */
+
+ /// What kind of resource this is.
core.String kind;
- /** The most likely class label (Categorical models only). */
+
+ /// The most likely class label (Categorical models only).
core.String outputLabel;
- /**
- * A list of class labels with their estimated probabilities (Categorical
- * models only).
- */
+
+ /// A list of class labels with their estimated probabilities (Categorical
+ /// models only).
core.List<OutputOutputMulti> outputMulti;
- /** The estimated regression value (Regression models only). */
+
+ /// The estimated regression value (Regression models only).
core.String outputValue;
- /** A URL to re-request this resource. */
+
+ /// A URL to re-request this resource.
core.String selfLink;
Output();
@@ -1278,7 +1342,9 @@ class Output {
outputLabel = _json["outputLabel"];
}
if (_json.containsKey("outputMulti")) {
- outputMulti = _json["outputMulti"].map((value) => new OutputOutputMulti.fromJson(value)).toList();
+ outputMulti = _json["outputMulti"]
+ .map((value) => new OutputOutputMulti.fromJson(value))
+ .toList();
}
if (_json.containsKey("outputValue")) {
outputValue = _json["outputValue"];
@@ -1289,7 +1355,8 @@ class Output {
}
core.Map<core.String, core.Object> toJson() {
- final core.Map<core.String, core.Object> _json = new core.Map<core.String, core.Object>();
+ final core.Map<core.String, core.Object> _json =
+ new core.Map<core.String, core.Object>();
if (id != null) {
_json["id"] = id;
}
@@ -1300,7 +1367,8 @@ class Output {
_json["outputLabel"] = outputLabel;
}
if (outputMulti != null) {
- _json["outputMulti"] = outputMulti.map((value) => (value).toJson()).toList();
+ _json["outputMulti"] =
+ outputMulti.map((value) => (value).toJson()).toList();
}
if (outputValue != null) {
_json["outputValue"] = outputValue;
@@ -1313,14 +1381,13 @@ class Output {
}
class Update {
- /**
- * The input features for this instance.
- *
- * The values for Object must be JSON objects. It can consist of `num`,
- * `String`, `bool` and `null` as well as `Map` and `List` values.
- */
+ /// The input features for this instance.
+ ///
+ /// The values for Object must be JSON objects. It can consist of `num`,
+ /// `String`, `bool` and `null` as well as `Map` and `List` values.
core.List<core.Object> csvInstance;
- /** The generic output value - could be regression or class label. */
+
+ /// The generic output value - could be regression or class label.
core.String output;
Update();
@@ -1335,7 +1402,8 @@ class Update {
}
core.Map<core.String, core.Object> toJson() {
- final core.Map<core.String, core.Object> _json = new core.Map<core.String, core.Object>();
+ final core.Map<core.String, core.Object> _json =
+ new core.Map<core.String, core.Object>();
if (csvInstance != null) {
_json["csvInstance"] = csvInstance;
}
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