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Cited by 307Text and Document Classification TechnologiesSentiment Analysis and Opinion MiningTopic Modeling

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Comparison of Naive Bayes, Random Forest, Decision Tree, Support Vector Machines, and Logistic Regression Classifiers for Text Reviews Classification

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Pranckevičius, Tomas, Marcinkevičius, Virginijus·2017·Baltic Journal of Modern Computing
DOI 10.22364/bjmc.2017.5.2.05
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Abstract

Today, a largely scalable computing environment provides a possibility of carrying out various data-intensive natural language processing and machine-learning tasks.One of these is text classification with some issues recently investigated by many data scientists.The authors of this paper investigate Naïve Bayes, Random Forest, Decision Tree, Support Vector Machines, and Logistic Regression classifiers implemented in Apache Spark, i.e. the in-memory intensive computing platform.The focus of the paper is on comparing these classifiers by evaluating the classification accuracy, based on the size of training data sets, and the number of n-grams.In experiments, short texts for product-review data from Amazon 1 were analyzed.

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Metadata

Authors
Pranckevičius, T., & Marcinkevičius, V.
Affiliations
Vilnius University (LT)
ORCID
Marcinkevičius, Virginijus
Venue
Baltic Journal of Modern Computing
Publisher
University of Latvia
Published
2017
Volume
5
Issue
2
ISSN
  • 2255-8942 (ISSN-L)
  • 2255-8950
DOI
10.22364/bjmc.2017.5.2.05
OpenAlex
W2726091402
Cited by
307
References
2
Citations by year
2026: 7 · 2025: 31 · 2024: 54 · 2023: 42 · 2022: 54 · 2021: 69 · 2020: 34 · 2019: 9 · 2018: 6
FWCI
7.99
Type
journal article
Language
en
Open access
Licence
cc-by-sa
Locations
Baltic Journal of Modern Computing (publishedVersion, cc-by-sa)
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › Text and Document Classification Technologies
  • Physical Sciences › Computer Science › Artificial Intelligence › Sentiment Analysis and Opinion Mining
  • Physical Sciences › Computer Science › Artificial Intelligence › Topic Modeling
Keywords
text classification, product reviews, classifier comparison, Apache Spark, in-memory computing, naive Bayes, random forest, decision tree, support vector machine, logistic regression, training data size, Amazon reviews

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