204,674 results for machine learning
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Journal Article
Contrasting Explain-ML with Interpretability Machine Learning Tools in Light of Interactive Machine Learning Principles
The way Complex Machine Learning (ML) models generate their results is not fully understood, including by very knowledgeable users. If users cannot interpret or trust the predictions generated by the model, they will not use them. Furthermore, the human role is often not properly considered in the…
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Journal Article Full text
A comprehensive machine learning approach for early detection of cardiovascular diseases using machine learning techniques
…Using the Framingham Heart Study dataset, this study assesses optimized machine learning techniques for CVD prediction. Class imbalance was addressed by a thorough preprocessing pipeline that included borderline-SMOTE2, partial record elimination, and feature standardisation. Accuracy, ROC-AUC…
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Secure Tiny Machine Learning on Edge Devices: A Lightweight Dual Attestation Mechanism for Machine Learning
…heavily on centralized servers, but advances in edge computing and Tiny Machine Learning (TinyML) now allow for on-device processing, enhancing battery efficiency and reducing latency. While this shift improves privacy, the distributed nature of edge devices introduces new security challenges…
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Determinants of Machine Learning Project Success: A Structural Equation Modeling Study of the Machine Learning Canvas
Machine learning (ML) project outcomes emerge from the interplay of organizational and technical subsystems. A recent study of 65 experienced data scientists reported that more than 80% of AI projects failed, roughly twice the failure rate of traditional IT projects, even as AI coding assistants…
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Journal Article
Credit card fraud classification using applied machine learning – a comparative study of 24 machine learning algorithms
…a novel framework for evaluating the collective performance of diverse machine learning (ML) models—including Logistic Regression, Decision Trees, Random Forests, Support Vector Machines, and Neural Networks—using a synthetic dataset carefully constructed to mirror real-world transaction features…
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Journal Article
A hybrid machine learning algorithm approach to predictive maintenance tasks: A comparison with machine learning algorithms
…This data can provide valuable insights into the behavior of a specific machine, enabling optimization or the prediction of potential malfunctions. Supervised machine learning algorithms are capable of predicting the remaining useful life (RUL) of a machine. However, there is room for improvement…
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Journal Article Full text
SIBILA: Automated Machine-Learning-Based Development of Interpretable Machine-Learning Models on High-Performance Computing Platforms
As machine learning (ML) transforms industries, the need for efficient model development tools using high-performance computing (HPC) and ensuring interpretability is crucial. This paper presents SIBILA, an AutoML approach designed for HPC environments, focusing on the interpretation of ML models…
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CAD models clustering with machine learning
…simultaneously. The vector of those features constituted an input for 3 machine learning algorithms: the random forest classifier, the support vector classifier and the fully connected neural network. The usefulness of the proposed approach was evaluated with a dataset consisting of over 1600 CAD…
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Neurocognition-inspired design with machine learning
Generating designs via machine learning has been an on-going challenge in computer-aided design. Recently, deep learning methods have been applied to randomly generate images in fashion, furniture and product design. However, such deep generative methods usually require a large number of training…
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Journal Article
Morphological Neuron Classification Using Machine Learning
…to classification and ii), to assess and compare the accuracy of machine learning algorithms to classify neuron morphologies. The algorithms were trained on 430 digitally reconstructed neurons subjectively classified into layers and/or m-types using young and/or adult development state population…
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Journal Article
Analog Algorithm – Landscapes of Machine Learning
In ihrem fotografischen Magazinbeitrag „Analog Algorithm – Landscapes of Machine Learning“, der auf ihrem gleichnamigen Buch basiert, nimmt uns die Fotografin Susanne Huth mit ins Silicon Valley, das Machtzentrum der technischen Innovation und der postindustriellen, neoliberalen Wirtschaftsordnung…
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Journal Article
People’s Councils for Ethical Machine Learning
Machine learning is a form of knowledge production native to the era of big data. It is at the core of social media platforms and everyday interactions. It is also being rapidly adopted for research and discovery across academia, business, and government. This article will explores the way the…
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Journal Article
Machine-learning Cosmology from Void Properties
…information about the laws and constituents of the Universe. We show that machine-learning techniques can unlock the information in void features for cosmological parameter inference. We rely on thousands of void catalogs from the GIGANTES data set, where every catalog contains an average of 11,000…
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Journal Article Full text
Corporate Default Forecasting with Machine Learning
We compare statistical models usually employed in credit risk forecasting with machine learning algorithms (ML). Using a large dataset which includes financial ratios and credit behavioral indicators for about 300,000 Italian non-financial firms from 2011 to 2017, we show that training the models…
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Journal Article
Machine Learning Assisted Cervical Cancer Detection
…formation. This paper proposes an approach named CervDetect that uses machine learning algorithms to evaluate the risk elements of malignant cervical formation. CervDetect uses Pearson correlation between input variables as well as with the output variable to pre-process the data. CervDetect uses…
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Journal Article Full text
Cartographing dynamic stall with machine learning
…outliers and analyze cycle-to-cycle variations. Modern data science and machine learning can be used to treat separated flows. In this study, a clustering method based on dynamic time warping is used to find different shedding behaviors. This method captures the fact that secondary and tertiary…
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