This documentation is for Machine Learner 1.0.0. View documentation for the latest release.
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The following are the REST APIs that are implemented in  WSO2 Machine Learner.

EntityOperationREST API
ConfigurationRetrieve data from WSO2 Data Analytics Server (DAS) tables GET /api/configs/das/tables
Retrieve all algorithmsGET /api/configs/algorithms
Retrieve a specific algorithmGET /api/configs/algorithms/{algorithmName}
Retrieve hyper parameters of an algorithmGET /api/configs/algorithms/{algorithmName}/hyperParams
Retrieve summary statistics settings of a datasetGET /api/configs/summaryStatSettings
Dataset Upload a datasetPOST /api/datasets
Retrieve all datasets GET /api/datasets
Retrieve all datasets and their versions for a given user GET /api/datasets/versions
Retrieve the dataset of a given dataset ID GET /api/datasets/{datasetId}
Retrieve all version sets of a dataset GET /api/datasets/{dataset_id}/versions
Retrieve version set ID of a given dataset versionGET /api/datasets/{dataset_id}/versions/{version}
Retrieve the dataset status of a given dataset ID GET /api/datasets/{datasetId}/status
Retrieve a version setGET /api/datasets/versions/{versionset_id}
Retrieve sample points of a given dataset version GET /api/datasets/versions/{versionsetId}/sample
Retrieve scatter plot points of the latest dataset version POST /api/datasets/{datasetId}/scatter
Retrieve scatter plot points of a dataset versionPOST /api/datasets/{versionset_id}/scatter
Retrieving chart sample points of the latest dataset version GET /api/datasets/{datasetId}/charts?features={feature_list}
Retrieve chart sample points of a given dataset version for a feature list GET /api/datasets/versions/{versionsetId}/charts?features={feature_list}
Retrieve Cluster points of a dataset for a feature listGET /api/datasets/{dataset_id}/cluster?features={feature_list}&noOfClusters={number_of_clusters}
Retrieve filtered feature names of a dataset GET /api/datasets/{datasetId}/filteredFeatures?featureType={featureType}
Retrieve summarized statistics of a feature in a datasetGET /api/datasets/{dataset_id}/stats?feature={feature_name}
Delete a datasetDELETE  /api/datasets/{dataset_id}
Delete a dataset version of a given dataset ID

DELETE /api/datasets/versions/{versionsetId}

Project Create a project (with a dataset name) POST /api/projects
Retrieve a project GET /api/projects/{name}
Retrieve all projectsGET /api/projects
Retrieve all models in a projectGET /api/projects/{project_id}/models
Retrieve all analyses of all projects GET /api/projects/analyses
Retrieve all analyses in a project GET /api/projects/{project_id}/analyses
Retrieve a specific analysis of a project GET /api/projects/{projectId}/analyses/{analysisName}
Delete a project DELETE /api/projects/{name}
Analysis (Workflow) Create a new analysis POST /api/analyses
Set customized features for an analysis POST /api/analyses/{id}/features
Load default features as customized features POST /api/analyses/{id}/features/defaults
Retrieve summarized features of an analysisGET /api/analyses/{analysisId}/summarizedFeatures
Retrieve customized features of an analysisGET /api/analyses/{analysisId}/customizedFeatures
Retrieve configurations of an analysisGET /api/analyses/{analysisId}/configs
Retrieve filtered features of an analysisGET /api/analyses/{analysisId}/filteredFeatures?featureType={featureType}
Retrieve features for an analysisGET /api/analyses/{analysisId}/features
Retrieve response variables of an analysisGET /api/analyses/{analysisId}/responseVariables
Retrieve the algorithm name of an analysisGET /api/analyses/{analysisId}/algorithmName
Retrieve the algorithm type of an analysisGET /api/analyses/{analysisId}/algorithmType
Retrieve the train data fraction of an analysisGET /api/analyses/{analysisId}/trainDataFraction
Retrieve the summarized statistics of an analysisGET /api/analyses/{analysisId}/stats?feature={featureName}
Set analysis configurations (e.g. algorithm type) POST /api/analyses/{id}/configurations
Setting hyper parameters for the selected algorithm of an analysisPOST /api/analyses/{id}/hyperParams
Retrieve hyper parameters of an analysisGET /api/analyses/{analysisId}/hyperParameters
Loading default hyper parameters for the selected algorithm of an analysisPOST /api/analyses/{id}/hyperParams/defaults
Retrieve all analyses GET /api/analyses
Retrieve all models of an analysisGET /api/analyses/{analysisId}/models
Delete an analysisDELETE /api/analyses/{id}
Model Create a model POST /api/models
Add model storage informationPOST /api/models/{id}/storages
Publish a modelPOST /api/models/{id}/publish
Make a prediction using a modelPOST /api/models/predict
Make prediction using a CSV/TSV filePOST /api/models/predictionStreams
Predict with a model POST /api/models/{id}/predict 
Retrieve a model GET /api/models/{name}
Retrieve all models GET /api/models
Delete a modelDELETE /api/models/{id}
Retrieve summary of a modelGET /api/models/{modelId}/summary
Export a modelGET /api/models/{name}/export
Build a modelPOST /api/models/{id}

The REST APIs are secured with basic authentication. Therefore, follow the steps below to add a basic auth header when calling these methods.

  1. Build a string of the form username:password.
  2. Encode the sting you created above using Base64. For encoding the above string using Base64, see Encode to Base64 format.
  3. Define an authorization header with the term "Basic_", followed by the encoded string. For example, the basic auth authorization header using "admin" as both username and password is as follows: 
    Authorization: Basic YWRtaW46YWRtaW4=
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