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WSO2 Machine Learner 1.1.0 includes revisions made to the REST API since the Machine Learner 1.0.0 release. These modifications include introducing new query parameters, changing path parameters, introducing new APIs etc. However, you can use the previous REST API version if required by making slight  modifications to the URI.

In ML 1.1.0, a user can invoke an API by providing the URI in the following three ways.

MethodExampleOutcome
Without specifying the version.https://localhost:9443/api/configs/algorithmsThe latest API version (i.e. V11) is invoked.
Specifying V10 as the version  
Specifying V11 as the version  

 

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}

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