Automated Text Binary Classification Using Machine Learning Approach

Holts, Alberto; Riquelme, Claudio; Alfaro, Rodrigo

doi:10.1109/sccc.2010.30

Cited by 6 publications

(7 citation statements)

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“…Genetic programming is an evolutionary algorithm that automatically evolves programs, functions, or any other type of symbolic expression, that carries out some type of calculation, to solve a specific task or problem [1], [3], [8]. Generally, these programs are represented as variable length structures such as a syntax tree.…”

Section: Genetic Programmingmentioning

confidence: 99%

“…The most common application of GP, perhaps, is the symbolic regression which attempts to find a mathematical expression that best fits a given set of training data (supervised learning) [3], [8]. So then, the goal is to find that expression K ^ O: R ^ n → R that fits a set T = {(x1, y1), ..., (xp, yp)} of p input/output data with xERn and yER and E {0,1} for a binary classification problem.…”

Section: Genetic Programmingmentioning

confidence: 99%

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A Genetic Programming Approach to Binary Classification Problem

Santoso¹,

Singh²,

Rajest³

et al. 2018

EAI Endorsed Transactions on Energy Web

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The Binary classification is the most challenging problem in machine learning. One of the most promising technique to solve this problem is by implementing genetic programming (GP). GP is one of Evolutionary Algorithm (EA) that used to solve problems that humans do not know how to solve it directly. The objectives of this research is to demonstrate the use of genetic programming in this type of problems; that is, other types of techniques are typically used, e.g., regression, artificial neural networks. Genetic programming presents an advantage compared to those techniques, which is that it does not need an a priori definition of its structure. The algorithm evolves automatically until finding a model that best fits a set of training data. Feature engineering was considered to improve the accuracy. In this research, feature transformation and feature creation were implemented. Thus, genetic programming can be considered as an alternative option for the development of intelligent systems mainly in the pattern recognition field.

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Section: Genetic Programmingmentioning

confidence: 99%

Section: Genetic Programmingmentioning

confidence: 99%

A Genetic Programming Approach to Binary Classification Problem

Santoso¹,

Singh²,

Rajest³

et al. 2018

EAI Endorsed Transactions on Energy Web

View full text Add to dashboard Cite

show abstract

“…The Naïve Bayes classifier is a probabilistic classifier that assumes the statistical independence of each feature (or word) and is a conditional model based on Bayes' formula [27] [28]. This classifier estimates the probabilities that an object from each class falls in each possible discrete value of vector variable x [29]. Then, Bayes theorem is used to generate classification.…”

Section: ) Naïve Bayesmentioning

confidence: 99%

Tax Complaints Classification on Twitter Using Text Mining

Dellia

Tjahyanto

2017

IJOS

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AbstractTwitter growth and utilization encourage the emergence of limitless textual information so that people can express their complaints easily This leads the Directorate General of Taxation uses twitter to deal with tax complaints faced by the community. However, the messages on twitter can contain any information, either the tax complaint or not. This will cause difficulties in handling complaints process. It is important to automatically identify so tax complaint handling can be done effectively and efficiently. Given these problems, it is necessary to do the twitter tax complaint classification with the support of text mining. There are several methods of classification such as Naïve Bayes classifiers, Support Vector Machine (SVM) and Decision Tree. This research aims to classify the tax complaint on twitter automatically by using text mining. The experimental results show the value of f-measure of SVM, Naïve Bayes and Decision Tree, respectively, are 89.3%, 85.6% and 76.9%.

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“…In an effort to better organize the information for users, researchers have been actively working the problem of automatic text categorization. Most of this work has focused on the categorization of categories, trying to sort the documents according to subject (Holts et al, 2010). However, recent years have grown rapidly in online discussion groups and sites reviews, where a crucial feature of the articles published is his way or global opinion on the subject, for example if a product review spoke positively or negatively (Pang & Lee, 2008).…”

Section: Automatic Classification Of Opinion (Sentiment Analysis)mentioning

confidence: 99%