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Catarina Palma, Artur Ferreira and Mário Figueiredo
The presence of malicious software (malware), for example, in Android applications (apps), has harmful or irreparable consequences to the user and/or the device. Despite the protections app stores provide to avoid malware, it keeps growing in sophisticat...
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Jayashree Piri, Puspanjali Mohapatra, Raghunath Dey, Biswaranjan Acharya, Vassilis C. Gerogiannis and Andreas Kanavos
The efficiency and the effectiveness of a machine learning (ML) model are greatly influenced by feature selection (FS), a crucial preprocessing step in machine learning that seeks out the ideal set of characteristics with the maximum accuracy possible. D...
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Monia Hamdi, Inès Hilali-Jaghdam, Manal M. Khayyat, Bushra M. E. Elnaim, Sayed Abdel-Khalek and Romany F. Mansour
Data mining (DM) involves the process of identifying patterns, correlation, and anomalies existing in massive datasets. The applicability of DM includes several areas such as education, healthcare, business, and finance. Educational Data Mining (EDM) is ...
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Jogeswar Tripathy, Rasmita Dash, Binod Kumar Pattanayak, Sambit Kumar Mishra, Tapas Kumar Mishra and Deepak Puthal
In high-dimensional data analysis, Feature Selection (FS) is one of the most fundamental issues in machine learning and requires the attention of researchers. These datasets are characterized by huge space due to a high number of features, out of which o...
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Manisha Sanjay Sirsat, Paula Rodrigues Oblessuc and Ricardo S. Ramiro
Genomic Prediction (GP) is a powerful approach for inferring complex phenotypes from genetic markers. GP is critical for improving grain yield, particularly for staple crops such as wheat and rice, which are crucial to feeding the world. While machine le...
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Zenab Mohamed Elgamal, Norizan Mohd Yasin, Aznul Qalid Md Sabri, Rami Sihwail, Mohammad Tubishat and Hazim Jarrah
The rapid growth in biomedical datasets has generated high dimensionality features that negatively impact machine learning classifiers. In machine learning, feature selection (FS) is an essential process for selecting the most significant features and re...
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Ibraheem Al-Jadir, Kok Wai Wong, Chun Che Fung and Hong Xie
Feature Selection (FS) methods have been studied extensively in the literature, and there are a crucial component in machine learning techniques. However, unsupervised text feature selection has not been well studied in document clustering problems. Feat...
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Jesús F. Pérez-Gómez, Juana Canul-Reich, José Hernández-Torruco and Betania Hernández-Ocaña
Requiring only a few relevant characteristics from patients when diagnosing bacterial vaginosis is highly useful for physicians as it makes it less time consuming to collect these data. This would result in having a dataset of patients that can be more a...
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Nikita Pilnenskiy and Ivan Smetannikov
With the current trend of rapidly growing popularity of the Python programming language for machine learning applications, the gap between machine learning engineer needs and existing Python tools increases. Especially, it is noticeable for more classica...
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Abdullateef Oluwagbemiga Balogun, Shuib Basri, Said Jadid Abdulkadir and Ahmad Sobri Hashim
Software Defect Prediction (SDP) models are built using software metrics derived from software systems. The quality of SDP models depends largely on the quality of software metrics (dataset) used to build the SDP models. High dimensionality is one of the...
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