Nowadays, large amount of data is available everywhere. Therefore, it is very important to analyse this data in
order to extract some useful information and to develop an algorithm based on this analysis. This can be achieved through
data mining and machine learning. Machine learning is an integral part of artificial intelligence, which is used to design
algorithms based on the data trends and historical relationships between data. Machine learning is used in various fields
such as bioinformatics, intrusion detection, Information retrieval, game playing, marketing, malware detection, image deconvolution
and so on. This paper presents the Necessity of Machine Learning and Role of Natural Language Processing in
Machine Learning, Classification of Machine Learning Algorithms, Role of Machine Learning in Deep Learning and its
Applications, A Comparison of Machine-Learning Classifiers, Multimodal Machine Learning, Deep Learning Based
Natural Language Processing, Natural Language Processing Generation, Integration of Predictive Intelligence with Social
Media Data. Implemented the Classification and Clustering Techniques and compared the results with EM Clustering
algorithm ,ZeroR algorithm and Random Forest Algorithm for the given attributes. It has taken less time when compared to
Random Forest and EM Clustering Algorithm.
Published In:IJCSN Journal Volume 8, Issue 1
Date of Publication : February 2019
Pages : 73-84
Figures :11
Tables : --
M Ashish Naidu :
Currently pursuing III B.Tech
Computer Science at GITAM University,Hyderabad. My Research
areas are Data Mining,Information Retrieval Systems,Big Data
Analytics,Machine Learning.
K Radha :
working as an Asst Professor at GITAM
University,Hyderabad. She has Completed M.Tech(CSE) at
JNTUH,Pursuing PhD at KL University,Vijayawada.She has 12
years of Teaching Experience and 1Year Industrial
Experience.She has published numerous research papers and
presented at Various conferences.She is a Member of IAENG.
Machine Learning, Deep Learning, Artificial Intelligence, Malware Detection, ZeroR, EM, Random Forest
algorithm, Classification, Clustering
Due to large amount of data is available everywhere.
Therefore, it is very important to analyse this data in order
to extract some useful information and to develop an
algorithm based on this analysis. Classification of Machine
Learning Algorithms, Role of Machine Learning in Deep
Learning and its Applications, A Comparison of Machine-
Learning Classifiers, Multimodal Machine Learning, Deep
Learning Based Natural Language Processing, Natural
Language Processing Generation, Integration of Predictive
Intelligence with Social Media Data. Implemented the
Classification and Clustering Techniques and compared
the results with EM Clustering algorithm ,ZeroR algorithm
and RandomForest Algorithm for the given attributes. It
has taken less time when compared to Random Forest and
EM Clustering Algorithm. Finally , ZeroR is the Best
algorithm Compared to EM and Random Forest
Algorithm.
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