Automatic Composition of Machine Learning Models as Web Services across Data Sets - HG, Mohan; M, Nandish; FV, Devaraj (International Journal of Computer Sciences and Engineering, 2022)
Machine Learning (ML) is a field of Artificial Intelligence, which applies the principles of statistics to predict the outcome of process by utilizing the historical data. Each ML model is built on a specific Data Set and programming language, however the knowledge obtained by the model is restricted to that particular Dataset. Web Service Composition (WSC) process of combining the available web services (WS) and arriving at a new web service based on the required inputs and preconditions. The paper presents an approach to represent a ML model as web service and automatically composing them with other ML models to utilize the knowledge gained on different data sets. The MLWSC approach consists of two stages. In stage one, semantic networks are created among the ML services to form a network. In stage two, MLWSC compositions are constructed based on the requirement of the user.