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Machine learning-based test smell detection
Test smells are symptoms of sub-optimal design choices adopted when develo** test cases. Previous studies have proved their harmfulness for test...
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A Review on Machine Learning and Deep Learning Based Systems for the Diagnosis of Brain Cancer
Brain cancer is a disease of the brain caused by a brain tumor. A brain tumor is the development of cells in the brain that grow in an unregulated...
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How good are machine learning clouds? Benchmarking two snapshots over 5 years
We conduct an empirical study of machine learning functionalities provided by major cloud service providers, which we call machine learning clouds ....
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A review of predictive uncertainty estimation with machine learning
Predictions and forecasts of machine learning models should take the form of probability distributions, aiming to increase the quantity of...
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Features of Detecting Malicious Installation Files Using Machine Learning Algorithms
AbstractThis paper presents a study of the possibility of using machine learning methods to detect malicious installation files related to the type...
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Predicting Liver Disorders Using an Extreme Learning Machine
Liver diseases are caused by excessive alcohol intake or viral infection. The liver can fail or develop cancer if it is not detected in its early...
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Machine Learning Opportunities in Flight Test: Preflight Checks
Flight test for aircraft certification is a fundamental method to ensure safe aircraft and air travel worldwide. Flight test data is collected...
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Generalisable sensor-free frustration detection in online learning environments using machine learning
Learning can generally be categorised into three domains, which include cognitive (thinking), affective (emotions or feeling) and psychomotor...
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Machine Learning Methods
This book provides a comprehensive and systematic introduction to the principal machine learning methods, covering both supervised and unsupervised...
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Early depression detection using ensemble machine learning framework
Social media platforms typically serve as generators of huge data sources as users express their sentiments directly or indirectly on these...
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Explanatory machine learning for sequential human teaching
The topic of comprehensibility of machine-learned theories has recently drawn increasing attention. Inductive logic programming uses logic...
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Machine learning and deep learning algorithms in detecting COVID-19 utilizing medical images: a comprehensive review
The public’s health is seriously at risk from the coronavirus pandemic. Millions of people have already died as a result of this devastating illness,...
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A survey on deep learning and machine learning techniques over histopathology image based Osteosarcoma Detection
Osteosarcoma is a common type of cancer that occurs in the cells and spreads to the bones. Osteosarcoma can develop due to genetic mutations, but...
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A Machine Learning Approach to Detect Lung Nodules Using Reinforcement Learning Based on Imbalanced Classification
Lung cancer is one of the fatal diseases affecting millions of people globally. Importantly, accuracy and rapid lung nodules detection on CT images...
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A Hybrid Machine Learning Model for Code Optimization
The complexity of programming modern heterogeneous systems raises huge challenges. Over the past two decades, researchers have aimed to alleviate...
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Skin cancer detection using ensemble of machine learning and deep learning techniques
Skin cancer is one of the most common forms of cancer, which makes it pertinent to be able to diagnose it accurately. In particular, melanoma is a...
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Predicting Renal Toxicity of Compounds with Deep Learning and Machine Learning Methods
Renal toxicity prediction plays a vital role in drug discovery and clinical practice, as it helps to identify potentially harmful compounds and...
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Machine learning for leaf disease classification: data, techniques and applications
The growing demand for sustainable development brings a series of information technologies to help agriculture production. Especially, the emergence...
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Explainable machine learning models for Medicare fraud detection
As a means of building explainable machine learning models for Big Data, we apply a novel ensemble supervised feature selection technique. The...
