Novel Evaluation Methodology for Machine Learning Algorithms through API Creation

Autor: Kantha Lakshmi Krishna Kumar, C N Soumya Amrita Kirthi, H. N. Suma
Rok vydání: 2019
Předmět:
Zdroj: COMSNETS
DOI: 10.1109/comsnets.2019.8711468
Popis: Datascientist have a need for API’s that can evaluate the standards of the code, test functionality of each feature involved in the execution of algorithms. It would be helpful if the datascientist can visualize these standards in an understandable form. In this reported work we present the details about one such API termed as score API. The score API takes input from the workbench, such as user name and password for authentication of the user, once authorized the user can check for status of the developed algorithm. API reports the strength of the algorithms and validates them through automation testing.
Databáze: OpenAIRE