INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
To analyze the behavior of various domains of data, sequence mining is an important task. The random forest algorithm, for example, can be used to extract patterns from data.Our main purpose in this paper is to compare the accuracy of various algorithms used in sequence analysis so far, such as SPADE, GPS, KNN, and Naive Bayesian.This paper is based on the research title: "Discover sequences using exceptional model mining and transition behavior".Even if the selection of data mining algorithm is domain specific the algorithms described must be compared to the accurate selection of algorithm that is suitable for the research.
This paper focuses on work done by various researchers.
Keywords:
Sequence mining,Pattern analysis, Naïve bayesian,EMM,Markov Process
Cite Article:
"A STUDY ON SEQUENCE MINING ALGORITHMS IN DATA RELATED TO EMM AND MARKOV PROCESS", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.8, Issue 10, page no.b268-b272, October-2023, Available :http://www.ijnrd.org/papers/IJNRD2310131.pdf
Downloads:
000118751
ISSN:
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Facebook Twitter Instagram LinkedIn