REST API Guide

The following are the REST APIs that are implemented in WSO2 Machine Learner.

Entity	Operation	REST API
Configuration	Retrieve data from WSO2 Data Analytics Server (DAS) tables	`GET /api/configs/das/tables`
	Retrieve all algorithms	`GET /api/configs/algorithms`
	Retrieve a specific algorithm	`GET /api/configs/algorithms/{algorithmName}`
	Retrieve hyper parameters of an algorithm	`GET /api/configs/algorithms/{algorithmName}/hyperParams`
	Retrieve summary statistics settings of a dataset	`GET /api/configs/summaryStatSettings`
Dataset	Upload a dataset	`POST /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 version	`GET /api/datasets/{dataset_id}/versions/{version}`
	Retrieve the dataset status of a given dataset ID	`GET /api/datasets/{datasetId}/status`
	Retrieve a version set	`GET /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 version	`POST /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 list	`GET /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 dataset	`GET /api/datasets/{dataset_id}/stats?feature={feature_name}`
	Delete a dataset	`DELETE` `/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 projects	`GET /api/projects`
	Retrieve all models in a project	`GET /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 analysis	`GET /api/analyses/{analysisId}/summarizedFeatures`
	Retrieve customized features of an analysis	`GET /api/analyses/{analysisId}/customizedFeatures`
	Retrieve configurations of an analysis	`GET /api/analyses/{analysisId}/configs`
	Retrieve filtered features of an analysis	`GET /api/analyses/{analysisId}/filteredFeatures?featureType={featureType}`
	Retrieve features for an analysis	`GET /api/analyses/{analysisId}/features`
	Retrieve response variables of an analysis	`GET /api/analyses/{analysisId}/responseVariables`
	Retrieve the algorithm name of an analysis	`GET /api/analyses/{analysisId}/algorithmName`
	Retrieve the algorithm type of an analysis	`GET /api/analyses/{analysisId}/algorithmType`
	Retrieve the train data fraction of an analysis	`GET /api/analyses/{analysisId}/trainDataFraction`
	Retrieve the summarized statistics of an analysis	`GET /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 analysis	`POST /api/analyses/{id}/hyperParams`
	Retrieve hyper parameters of an analysis	`GET /api/analyses/{analysisId}/hyperParameters`
	Loading default hyper parameters for the selected algorithm of an analysis	`POST /api/analyses/{id}/hyperParams/defaults`
	Retrieve all analyses	`GET /api/analyses`
	Retrieve all models of an analysis	`GET /api/analyses/{analysisId}/models`
	Delete an analysis	`DELETE /api/analyses/{id}`
Model	Create a model	`POST /api/models`
	Add model storage information	`POST /api/models/{id}/storages`
	Publish a model	`POST /api/models/{id}/publish`
	Make a prediction using a model	`POST /api/models/predict`
	Make prediction using a CSV/TSV file	`POST /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 model	`DELETE /api/models/{id}`
	Retrieve summary of a model	`GET /api/models/{modelId}/summary`
	Export a model	`GET /api/models/{name}/export`
	Build a model	`POST /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.

Build a string of the form username:password.
Encode the sting you created above using Base64. For encoding the above string using Base64, see Encode to Base64 format.
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=