User Knowledge Modelling Through Azure Machine Learning Studio

In today’s world scenario where everyone is able to access and learn different skillsets, it gets difficult for the companies to segregate the employees based on the level of knowledge they pose. In remedy to this problem a machine learning classification model has been proposed, in order to segregate the employees based on the level of knowledge they pose. For building this model automated machine learning is employed through azure machine learning studio. Existing ‘classification algorithms’ used to classify the employees in different classes and also to compare the results and analysis to demonstrate which algorithm performs better. The algorithms used for this task were: Multi-class Logistic Regression and Multi-class Decision Forest. The average accuracy from the algorithms were: 85.71% and 97.40% respectively. Model is capable to be used in the industry in order to segregate their employees into different sections and take advantage of their knowledge level in different fields, and also by colleges in their grading system for relative marking.