Skip to content

shrikanthn/karma-decision-tree-service

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

14 Commits
 
 
 
 
 
 
 
 

Repository files navigation

Karma-Decision-Tree-Service

A RESTful service for Decision Tree implementation 'rpart' in R.

Setting up the service

  • Compile and create WAR file:

    • Open Terminal and go to dt-service folder
    • Run mvn clean package
  • Copy the WAR file from dt-service/target/ to webapps folder of Tomcat

  • Start the Tomcat server

Running the service

  • To train and create a Decision Tree model:

    • Send a POST request with payload as contents of the training data in CSV format to

      http://host-name:port/dt-service/api/dt/train

    • By default, the last column is assumed to contain the class labels

    • To specify column-number of class labels, add classColumnNumber parameter:

      http://host-name:port/dt-service/api/dt/train?classColumnNumber=column-number

    • The response will contain a summary of the training phase and the name of the created model at its bottom

    • Note down the model name (which starts with 'DT' and ends with 'model')

  • To test a model:

    • Send a POST request with payload as contents of the testing data in CSV format to

      http://host-name:port/dt-service/api/dt/test?modelName=model-name

    • To specify column-number of class labels, add classColumnNumber parameter:

      http://host-name:port/dt-service/api/dt/test?modelName=model-name&classColumnNumber=column-number

    • By default, the output of the testing phase is a confusion matrix

    • To specify the output type of the testing phase, add outputType parameter:

      • http://host-name:port/dt-service/api/dt/test?modelName=model-name&outputType=confusion_matrix
      • http://host-name:port/dt-service/api/dt/test?modelName=model-name&outputType=predictions

About

karma-decision-tree-service

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published