An Empirical Research Approach on Confusion Matrix Using Existing Musical Industry Dataset

An Empirical Research Approach on Confusion Matrix Using Existing Musical Industry Dataset

Dr R.Naveenkumar, Associate Professor, Department of Computer Science and Engineering Brainware University Kolkata WestBengal

E-Mail: rnaveenkumarooty@gmail.com

Shubhadeep Pandit, Department of Computer Science and Engineering Brainware University Kolkata WestBengal

Abstract :

This paper analyzes the sales of existing music albums from 1973 to 2019. The data shows that the music industry has experienced many changes over the years, with the most significant change being the introduction of digital platforms. Digital platforms have disrupted the traditional music industry model, leading to a decline in sales of physical albums. The paper also analyzes the sales of each medium through which music was distributed worldwide with different machine learning algorithm classifiers consistently exhibiting inadequate predictive power. the lack of a good prognosis highlights a fundamental failure toward well-infected persons in a class. the presence of non-zero false positive rates indicates negative data are distributed among positive errors. analysis of the data reveals worrying inefficiencies in classifier performance

Keywords: Precession, Recall, Accuracy, Track, Digital industry, Cost efficiency and confusion matrix