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Retrieving All Algorithms via REST API v10
Overview
Description | Retrieve all algorithms. |
Resource Path |
|
HTTP Method | GET |
Request/Response Format | application/json |
Sample cURL command
curl -H "Content-Type: application/json" -H "Authorization: Basic YWRtaW46YWRtaW4=" -v https://localhost:9443/api/v10/configs/algorithms -k
Example
GET https://localhost:9443/api/v10/configs/algorithms
Sample output
[ { "interpretability":5, "scalability":5, "multicollinearity":1, "dimensionality":5, "name":"LINEAR_REGRESSION", "type":"Numerical_Prediction", "parameters":[ { "value":"100", "key":"Iterations", "description":"Number of times optimizer runs before completing the\n\t\t\t\t\toptimization process. This parameter value should be an integer\n\t\t\t\t\tgreater than 0.\n\t\t\t\t" }, { "value":"0.001", "key":"Learning_Rate", "description":"Step size of the optimization algorithm. This parameter\n\t\t\t\t\tvalue should be between 0 and 1, 1 inclusive.\n\t\t\t\t" }, { "value":"1", "key":"SGD_Data_Fraction", "description":"Fraction of the training dataset used per iteration\n\t\t\t\t\tin the optimization algorithm. This parameter value should be\n\t\t\t\t\tbetween 0 and 1, 1 inclusive.\n\t\t\t\t" } ] }, { "interpretability":5, "scalability":5, "multicollinearity":1, "dimensionality":5, "name":"RIDGE_REGRESSION", "type":"Numerical_Prediction", "parameters":[...] } ]