A review of android malware detection approaches based on machine learning
K Liu, S Xu, G Xu, M Zhang, D Sun, H Liu - IEEE access, 2020 - ieeexplore.ieee.org
Android applications are develo** rapidly across the mobile ecosystem, but Android
malware is also emerging in an endless stream. Many researchers have studied the …
malware is also emerging in an endless stream. Many researchers have studied the …
A review of feature selection and its methods
Nowadays, being in digital era the data generated by various applications are increasing
drastically both row-wise and column wise; this creates a bottleneck for analytics and also …
drastically both row-wise and column wise; this creates a bottleneck for analytics and also …
A review of feature selection methods with applications
Feature selection (FS) methods can be used in data pre-processing to achieve efficient data
reduction. This is useful for finding accurate data models. Since exhaustive search for …
reduction. This is useful for finding accurate data models. Since exhaustive search for …
Feature selection with multi-view data: A survey
This survey aims at providing a state-of-the-art overview of feature selection and fusion
strategies, which select and combine multi-view features effectively to accomplish …
strategies, which select and combine multi-view features effectively to accomplish …
A survey on feature selection methods
Plenty of feature selection methods are available in literature due to the availability of data
with hundreds of variables leading to data with very high dimension. Feature selection …
with hundreds of variables leading to data with very high dimension. Feature selection …
[PDF][PDF] Feature selection
Relevant feature identification has become an essential task to apply data mining algorithms
effectively in real-world scenarios. Therefore, many feature selection methods have been …
effectively in real-world scenarios. Therefore, many feature selection methods have been …
Tutorial on practical tips of the most influential data preprocessing algorithms in data mining
Data preprocessing is a major and essential stage whose main goal is to obtain final data
sets that can be considered correct and useful for further data mining algorithms. This paper …
sets that can be considered correct and useful for further data mining algorithms. This paper …
Data mining: practical machine learning tools and techniques with Java implementations
Witten and Frank's textbook was one of two books that 1 used for a data mining class in the
Fall of 2001. The book covers all major methods of data mining that produce a knowledge …
Fall of 2001. The book covers all major methods of data mining that produce a knowledge …
Multitask learning
Multitask Learning is an approach to inductive transfer that improves generalization by using
the domain information contained in the training signals of related tasks as an inductive bias …
the domain information contained in the training signals of related tasks as an inductive bias …
Correlation-based feature selection for machine learning
MA Hall - 1999 - researchcommons.waikato.ac.nz
A central problem in machine learning is identifying a representative set of features from
which to construct a classification model for a particular task. This thesis addresses the …
which to construct a classification model for a particular task. This thesis addresses the …