International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 08 Issue: 02 | Feb 2021 www.irjet.net p-ISSN: 2395-0072
© 2021, IRJET | Impact Factor value: 7.529 | ISO 9001:2008 Certified Journal | Page 338
A Survey of Design an Approach for Prediction of Music System
Neelu Sharma
1
, Rajesh Boghey
2
, Sandeep Rai
3
1
M.Tech Scholar, Department of CSE, TIT Excellence, Bhopal (M.P), India
1
2
Assistant Professor, Department of IT, TIT, Excellence, Bhopal (M.P), India
2
3
Professor & Head, Department of IT, TIT, Excellence, Bhopal (M.P), India
3
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ABSTRACT
: Data mining and machine learning is very necessary and
very relevant acts from last decade now this data mining is
shifted to Machine Learning. Machine Learning comes by
Artificial Intelligence and Mathematical Stats. Machine
learning is classified into supervised, unsupervised and
reinforcement. In this Paper Authors explains with the
progress of technology in music players, especially in
inventive cell phones, users have access to large archives.
Here we analyse the music portal KKBOX in this work we
analyse the different dependent attributes their behaviour
and others. Authors used here many algorithms to create
different model so that after comparison of different model
we can able to say that which will give better result for
given data or similar type of data.
Keywords: Classification Algorithm, Machine Learning, Deep
Learning, Decision Tree & Random Forest, ensemble
Techniques, CNN.
I. INTRODUCTION
We know that Data is very crucial item for any industries.
We are concentrating over data from 18
th
century. Then in
19
th
century computer was evolved after then importance
of data is increasing day by day. With the time many
technologies come into existence like Database,
Datamining, machine learning & Deep learning. We know
that the above technology needs abundant amount of data.
The use of this work is basically we can detect the
prediction of music by any prediction system. We know
that rating is very important these days every industry is
concentrated the reviews and rating of any product.
Previous knowledge will help to predict any behaviour in
songs, types of songs, authors etc.
Figure 1: Journey of Data Science
1.1 Data Mining Process
Data mining process contains many steps like Data
cleaning, Data integration, Data selection, Data
transformation, Data mining, Pattern evaluation,
Knowledge presentation.
Figure 2: Process of Data Mining
Since we know that data mining process is complex process
where we have to apply number of intermediate process.
During Intermediate process we concentrate that how data
can be filter or refine to the pattern generation.
1.2 Data Mining Techniques
Data mining Algorithms is categorized into different which
is given below:
DATA SELECTION
PRE-PROCESSING
TRANSFORMATION
DATA MINING
DATA VISUALIZATION
Statistics (18
th
Century)
Computer Science Evolve (19
th
Century)
Data Base, Data-Ware Houses & Mining
AI, Data Science & Machine Learning