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Sequential Data Classification under Dynamic Emission
AbstractSequential data are ubiquitous and widely available in a range of applications in almost all areas. We aim at considering medical,...
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Online binary classification from similar and dissimilar data
Similar-dissimilar (SD) classification aims to train a binary classifier from only similar and dissimilar data pairs, which indicate whether two...
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Skyline query under multidimensional incomplete data based on classification tree
A method for skyline query of multidimensional incomplete data based on a classification tree has been proposed to address the problem of a large...
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Kent feature embedding for classification of compositional data with zeros
Compositional data have posed challenges to current classification methods owing to the non-negative and unit-sum constraints, especially when a...
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Data reweighting net for web fine-grained image classification
Fine-grained visual classification (FGVC) necessitates expert knowledge,which is expensive and requires a large training sample size. Consequently,...
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Missing data imputation and classification of small sample missing time series data based on gradient penalized adversarial multi-task learning
In practice, time series data obtained is usually small and missing, which poses a great challenge to data analysis in different domains, such as...
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An automated approach for binary classification on imbalanced data
Imbalanced data are present in various business sectors and must be handled with the proper resampling methods and classification algorithms. To...
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Nonparametric System for Automatic Classification of Large-Scale Statistical Data
AbstractThe structure of a nonparametric system for automatic classification of large-scale statistical data is proposed and substantiated. The...
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Real-Time Multi-Class Classification of Respiratory Diseases Through Dimensional Data Combinations
In recent times, there has been active research on multi-disease classification that aim to diagnose lung diseases and respiratory conditions using...
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Classification and Data Science in the Digital Age
The contributions gathered in this open access book focus on modern methods for data science and classification and present a series of real-world...
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Random Subspace Sampling for Classification with Missing Data
Many real-world datasets suffer from the unavoidable issue of missing values, and therefore classification with missing data has to be carefully...
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A new technique for classification method with imbalanced training data
Imbalanced classification is a very common and crucial challenge in the machine learning domain. Due to unequal instances in different classes, the...
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Data Augmentation for Traffic Classification
Data Augmentation (DA)—enriching training data by adding synthetic samples—is a technique widely adopted in Computer Vision (CV) and Natural Language...
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Lost in data: recognizing type of time series sensor data using signal pattern classification
With the increase in number and size of Internet of Things systems, there is an ever-growing risk of (meta)data loss, as well as the maintenance...
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Data complexity measures for classification of a multi-concept dataset
Classification algorithms design predictive models that classify data under one of the predefined categories. The data can be text, image, audio,...
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Data-driven operator functional state classification in smart manufacturing
One of the main challenges in the industry is having trained and efficient operators in manufacturing lines. Smart adaptive guidance systems are...
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Superpixelwise PCA based data augmentation for hyperspectral image classification
Data Augmentation (DA) is significant for Hyperspectral Image (HSI) classification especially in the case of limited labeled training data. Various...
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Feature reduction of unbalanced data classification based on density clustering
With the development of big data, the problem of imbalanced data sets is becoming more and more serious. When dealing with high-dimensional...
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A color constancy based flower classification method in the blockchain data lake
The efficient classification of flower images will directly affect the accuracy of their automatic recognition. Due to the complexity of the...
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Streaming traffic classification: a hybrid deep learning and big data approach
Massive amounts of real-time streaming network data are generated quickly because of the exponential growth of applications. Analyzing patterns in...
