URI

<machinelearning_uri>/ml-process:LinearSVCFit[.<format>]

Supported methods

GET、POST、HEAD

Parent resource

machineLearning

Introduction

对空间数据进行支持向量机分类训练。

Supported methods:

  • GET：Returns an interactive operation page for analysis.
  • POST：Executes the analysis.
  • HEAD：检查datasourceresource exists, or if there is permission to accessdatasource资源。

Supported output formats:JSONP、RJSON、JSON、HTML、XML。

GIS Services Resource Hierarchy

 

HTTP Request Methods

Perform an HTTP request on the following URI. Here, supermapiserver is the server name.

http://supermapiserver:8090/iserver/iserver/services/machinelearning/restjsr/sps.WorkflowProcessFactory.models.ml-process:linearsvcfit

GET 请求

Returns an interactive operation page for analysis.

 

POST 请求

Executes the analysis.

请求参数

Request parameter list:

Field Type Definition

readasfeaturerdd-dataConnInfo

[Required]

String

Training dataset, which needs to include data type, connection parameters, dataset name, etc.

readasfeaturerdd-filter

[Optional]

String

Data query conditions

dependent

[Required]

String

Modeling field

explanatory

[Required]

String

 解释字段，该集合输入训练数据集的一个或多个字段名称作为模型的解释变量。

maxIter

[Optional]

String

 最大迭代次数，取值范围>0，默认值为100。

regParam

[Optional]

String

 正则化参数，正则化主要用于防止过拟合现象，取值范围≥0，默认值为0.0。

explanatoryDistanceRDDs

[Optional]

String

Distance explanatory variable dataset, supporting point, line, and region datasets.

modelPath

[Optional]

String

 模型保存目录

HEAD 请求

Returns the same HTTP response headers as a GET request, but without the response body. This allows retrieving meta-information from the response headers without transporting the entire content. The meta-information includes the media type,字符编码，压缩编码，实体内容长度等。

A HEAD request can be used to check if linearSVCFit 资源是否存在，或者客户端是否有权限访问 linearSVCFit 资源。通过对加.<format>的 URI 执行 HEAD 请求，还可以快速判断 linearSVCFit 资源是否支持<format>格式的表述。

See