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Many conventional statistical and machine learning methods face challenges when applied directly to high dimensional temporal observations. In recent decades, Functional Data Analysis (FDA) has gained widespread popularity as a framework for ...

The adoption of the Internet of Things (IoT) has proliferated across various domains, where everyday objects like refrigerators and washing machines are now equipped with sensors and connected to the internet. Undeniably, the security of such ...

• Propose a fake review detection method based on the general mixed probability.
• Generate review data more effectively than several well-known sampling algorithms.
• Yield accurate detection using content, behavioral and ...

Online consumer reviews play an important role in helping consumers judge the quality and authenticity of products on e-commerce platforms. However, the constant presence of fake reviews on these platforms has significantly impacted the operation ...

• A new DL-based supervised classification method is proposed that utilizes multiple undercomplete dictionaries.

In dictionary-learning-based classification methods, a given data point is classified based on its representation over one or possibly more learned dictionaries. The goal is to find dictionaries that minimize the classification error. ...

It is found that, chronic kidney disease (CKD) is prevalence worldwide. Quality of life (QoL) in terms of health became an essential measure for patients with CKD. This paper uses the real-time dataset of CKD patients collected from reputed ...

Explainability is essential for users to effectively understand, trust, and manage powerful artificial intelligence solutions. Decision trees are one of the pioneer explanaible artificial intelligence algorithms widely used by experts ...

Methods to classify objects into two or more classes are at the core of various disciplines. When a set of objects with their true classes is available, a supervised classifier can be trained and employed to decide if, for example, a new patient has ...

Depth functions offer an array of tools that enable the introduction of quantile- and ranking-like approaches to multivariate and non-Euclidean datasets. We investigate the potential of using depths in the problem of nonparametric supervised ...

In this paper we present a novel mathematical optimization-based methodology to construct tree-shaped classification rules for multiclass instances. Our approach consists of building Classification Trees in which, except for the leaf nodes, the ...

Identifying small dolphin species based on their vocalizations remains a challenging task due to their similar vocal signatures and frequency modulation patterns, particularly when the available data sets are relatively limited. To address this ...$\mathrm{}$

• The partial label ranking problem is an exciting learning scenario for non-standard supervised classification problems (e.g., multi-label).

The partial label ranking problem is a particular preference learning scenario that focuses on learning preference models from data, such that they predict a complete ranking with ties defined over the values of the class variable for ...

Real-world problems are commonly characterized by a high feature dimensionality, which hinders the modelling and descriptive analysis of the data. However, some of these data may be irrelevant or redundant for the learning process. Different ...

Feature Selection (FS) is considered a crucial step in machine learning and data mining tasks, which facilitates minimizing the direct consequence of redundant and irrelevant attributes on the model’s accuracy. Hence, the researchers ...

• Improved Binary AO (IBAO) is proposed with random position amendment and LS strategy.

• CNN architecture called MSFA-Net that acts as a texture feature extractor from raw images.
• MSFA-Net requires to learn much fewer hyperparameters than state-of-the-art CNNs, and so reduces computation costs.
• MSFA-Net outperforms ...

Multispectral snapshot cameras fitted with a multispectral filter array (MSFA) acquire several spectral bands in one shot and provide a raw mosaic image in which a single channel value is available at each pixel. Texture features are classically ...

• Support Vector Machines (SVMs) are a popular kernel method for supervised learning.

For supervised classification tasks that involve a large number of instances, we propose and study a new efficient tool, namely the Local-to-Global Support Vector Machine (LGSVM) method. Its background somehow lies in the framework of ...

In this study, we evaluated the use of synthetic aperture radar (SAR) and multispectral data to detect aquaculture waterbodies in Southern Bangladesh to quantify fish production on a national scale. For this purpose, we developed an ...

• Information about rapidly growing aquaculture in developing countries is limited.

In this paper we propose novel methodologies to optimally construct Support Vector Machine-based classifiers that take into account that label noise occur in the training sample. We propose different alternatives based on solving Mixed ...

• We present mathematical programming approaches to classify datasets with noisy labels.

Skin diseases are the most important worrying problems in societies because it affects the patients both physically and psychologically. Skin disease is one of the highly prone to risk with an association of climatic factors around the world. ...

Decision trees (DTs) are popular classifiers partly due to their reasonably good classification performance, their ease of interpretation, and their widespread use in ensembles. To improve the classification performance of individual ...

• We introduce the Functional Tree for class imbalance problems (FT4cip).
• We make ...

• Moldy core is a serious disease that influences the quality of pears.
• Online full-transmittance Vis/NIR spectroscopy is feasible to class of moldy pears.
• BOSS-SPA is excellent to optimize variables for classification of moldy core ...

Moldy core is a serious disease that influences the quality of pears. There is no apparent difference between the diseased and sound fruit because this kind of disease mainly occurs in core of pears. In automatic detection and grading of pear ...