EEG_WebServer

Web server built using Spring Boot that creates EEG data analysis jobs, check their status and get the result over a REST API.

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The server listens for requests:

• /jobs/submit/(id)?{qp}
  - to submit a job with configuration specified in the query parameters
• /jobs/check/(id)
  - to check the status of a job with id=={id} -> either RUNNING OR FINISHED
• /jobs/result/(id)
  - to get the result output of a job with id=={id}
• /jobs/log/{id}
  - to get the log of a job with id=={id}
• /jobs/cancel/{id}
  - to cancel a job with id=={id}
• /jobs/configuration/{name}
  - to get the configuration of a job with id=={id}
• /classifiers/list
  - to list all the saved classifiers

where the {id} or {name} are path variables provided by the client, and {qp} are query parameters that configure the spark application.

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Requirements

Java 6+
Open port: 8990
Place the Data Analysis Package in the same directory as this JAR file

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The supported query parameters are:

0. Id (REQUIRED - the id of the job)

• id = {some_integer}*

1. Input file (REQUIRED - choose what type of input you want to provide)

• info_file={*path_to_file}
  OR
• eeg_file={*path_to_file} AND guessed_num={*number}

2. Feature extraction (REQUIRED - choose the method used for classification)

• fe = {dwt-8}

3. Classification

• a) (REQUIRED - choose whether to train or load a classifier)
  train_clf = {svm,dt,logreg,rf}
  OR
  load_clf={svm,dt,logreg,rf} AND load_name={src/main/resources/Classifiers/(name) }

• b) (OPTIONAL - choose whether to save the classifier and give him a name)
  save_clf={true,false}
  AND
  save_name={*name}

• c) (REQUIRED - the specific configuration for each classifier)
  config_clf_param -> can't be condensed as it's very specific for each classifier

4. Saving the results (REQUIRED - choose where to save the classifier performance)

• result_path={*path_to_file}