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Data cleaning and machine learning: a systematic literature review
Machine Learning (ML) is integrated into a growing number of systems for various applications. Because the performance of an ML model is highly...
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Parameterized Clustering Cleaning Approach for High-Dimensional Datasets with Class Overlap and Imbalance
Software Defect Prediction (SDP) uses machine learning algorithms to detect faulty and defective modules inside software projects. Like any machine...
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Dirty Data Processing for Machine Learning
In both the database and machine learning communities, data quality has become a serious issue which cannot be ignored. In this context, we refer to...
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Survival Factors Analysis of Out-of-Hospital Cardiac Arrest Patients via Effective Data Cleaning Techniques and Explainable Machine Learning
The purpose of this study is to explore the key survival factors of OHCA (Out-of-Hospital Cardiac Arrest) non-trauma cases through data science...
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An efficient and lightweight small target detection framework for vision-based autonomous road cleaning
The development of machine vision technology provides a feasible way for intelligent vehicles used for road cleaning to achieve automation, improve...
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A Review: Dust Cleaning Approach of Solar Photovoltaic System Using IOT & ML
Governments have been pushed to boost the installation of Non-Conventional Energy Sources as a outcome of rising energy need and trouble about global...
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Noise cleaning for nonuniform ordinal labels based on inter-class distance
Label noise poses a significant challenge to supervised learning algorithms. Extensive research has been conducted on classification and regression...
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Covid-19 Data Preprocessing Approach in Machine Learning for Prediction
Artificial Intelligence (AI) is a vast field that allows the development of programs capable of simulating human intelligence. One of the most used...
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Single-tag and multi-tag RFID data cleaning approach in edge computing
As the performance of Radio Frequency Identification (RFID) devices is susceptible to the influence of the surrounding environment, making the...
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Cleaning of object surfaces based on deep learning: a method for generating manipulator trajectories using RGB-D semantic segmentation
A mobile robot with a robotic arm needs to be able to autonomously perceive the operating environment and plan the trajectory of the object’s surface...
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Fundamentals of Evolutionary Machine Learning
In this opening chapter, we overview the quickly develo** field of evolutionary machine learning. We first motivate the field and define how we...
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Using particle size distributions to identify indoor emissions: a machine learning method for source recognition
Variation in emitted particle sizes between sources offers potential for source identification. Seven thousand two hundred particle size...
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Autocleandeepfood: auto-cleaning and data balancing transfer learning for regional gastronomy food computing
Food computing has emerged as a promising research field, employing artificial intelligence, deep learning, and data science methodologies to enhance...
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Machine Learning Technology
Machine learning, precisely referred to as ML, is a sub-domain of artificial intelligence (AI) technology. Artificial Intelligence is a large field...
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A machine learning approach to predict geomechanical properties of rocks from well logs
The estimation of geomechanical properties such as Young’s modulus from well logs is a crucial task in the field of geomechanical engineering....
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Python for Machine Learning
Machine learning is a sub-field of artificial intelligence capable of giving intelligent solutions to real-world problems. It is data-driven...
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Towards optimized machine-learning-driven intrusion detection for Internet of Things applications
As the utilization of Internet of Things devices becomes increasingly important in real-life applications, the need to address potential threats to...
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Machine Learning
Machine learning is currently a mainstream research hotspot in the AI industry, entailing multiple disciplines such as probability theory,...
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Classification of Toxic Comments on Social Networks Using Machine Learning
This research addresses the problem of toxic comments in social networks, and how artificial intelligence (AI) and machine learning (Machine...
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Artificial intelligence and edge computing for machine maintenance-review
Industrial internet of things (IIoT) has ushered us into a world where most machine parts are now embedded with sensors that collect data. This huge...
