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Journal of Applied Science and Technology Trends
Scopus
ISSN 2708-0757 · 5 artikel di indeks
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Artikel Jurnal Teks lengkap
Multimodal Emotion Recognition using Deep Learning
New research into human-computer interaction seeks to consider the consumer's emotional status to provide a seamless human-computer interface. This would make it possible for people to survive and be used in widespread fields, including education and medicine. Multiple techniques can be defined…
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Artikel Jurnal Teks lengkap
The Role of Machine Learning Algorithms for Diagnosing Diseases
Nowadays, machine learning algorithms have become very important in the medical sector, especially for diagnosing disease from the medical database. Many companies using these techniques for the early prediction of diseases and enhance medical diagnostics. The motivation of this paper is to give an…
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Artikel Jurnal Teks lengkap
Classification Based on Decision Tree Algorithm for Machine Learning
Decision tree classifiers are regarded to be a standout of the most well-known methods to data classification representation of classifiers. Different researchers from various fields and backgrounds have considered the problem of extending a decision tree from available data, such as machine study…
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Artikel Jurnal Teks lengkap
A Review on Linear Regression Comprehensive in Machine Learning
Perhaps one of the most common and comprehensive statistical and machine learning algorithms are linear regression. Linear regression is used to find a linear relationship between one or more predictors. The linear regression has two types: simple regression and multiple regression (MLR). This…
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Artikel Jurnal Teks lengkap
A Comprehensive Review of Dimensionality Reduction Techniques for Feature Selection and Feature Extraction
Due to sharp increases in data dimensions, working on every data mining or machine learning (ML) task requires more efficient techniques to get the desired results. Therefore, in recent years, researchers have proposed and developed many methods and techniques to reduce the high dimensions of data…