Operational Business Prediction System using Machine Learning Algorithm.

Abstract

Every professional organization looks for growth and development with the passage of time. But here we find only a handful of business organizations that effectively represent this vision do so via decision making algorithms using diverse datasets. And to win firm control over such decisions, machine learning models and predictive analysis plays a vital role.

Machine learning models and predictive analytics forecasts upcoming conclusions based on the collected historical or current but related datasets. Machine Learning and data analytics were considered two separate branches for long period of time. But due to their importance felt by the data scientists, both machine learning and data analytics are considered the two sides of the same coin. Machine Learning algorithms and analytics have transformed the world into completely new modern high-tech era. In this research work an effective machine learning model is proposed that aims to predict the class of unknown case related to business organization using K-Nearest Neighbor classification algorithm. In this experimental work, model 1 and model 2 are formulated based on train-test split ratio. However a comparative study is executed which portrays that model 2 over powers to model 1 in performance measures related to business problems.