204.674 hasil untuk machine learning
Menampilkan 501–520 · 0,73 detik · RSS
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Artikel Jurnal
Artificial intelligence/machine learning in diabetes care
Artificial intelligence/Machine learning (AI/ML) is transforming all spheres of our life, including the healthcare system. Application of AI/ML has a potential to vastly enhance the reach of diabetes care thereby making it more efficient. The huge burden of diabetes cases in India represents a…
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Artikel Jurnal
Machine learning techniques in dialogue act recognition
…to determine the intention of the speaker, in dialogue systems with machine translation to resolve ambiguities in the possible translation variants and in speech recognition to reduce word recognition error rate. Several recognition techniques are described on the surface level: how they work and…
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Artikel Jurnal
Durum wheat yield forecasting using machine learning
A reliable and accurate forecasting model for crop yields is crucial for effective decision-making in every agricultural sector. Machine learning approaches allow for building such predictive models, but the quality of predictions decreases if data is scarce. In this work, we proposed…
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Artikel Jurnal Teks lengkap
Applying Machine Learning to Software Fault Prediction
…the preliminary research. Methods: It has been demonstrated that using machine learning techniques, it is possible to predict faults for C/C++ and Java projects with recall 0.71 and false positive rate 0.25. A similar approach was applied in order to find out if promising results can be obtained…
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Artikel Jurnal
Perspectives in machine learning for wildlife conservation
Animal ecologists are increasingly limited by constraints in data processing. Here, Tuia and colleagues discuss how collaboration between ecologists and data scientists can harness machine learning to capitalize on the data generated from technological advances and lead to novel modeling approaches.
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Artikel Jurnal
Predicting anesthetic infusion events using machine learning
Abstract Recently, research has been conducted to automatically control anesthesia using machine learning, with the aim of alleviating the shortage of anesthesiologists. In this study, we address the problem of predicting decisions made by anesthesiologists during surgery using machine learning…
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Artikel Jurnal
Prediction of antifreeze proteins using machine learning
…Scoring Matrix Tri-Slicing (PseTS-PSSM). Keeping the benefits of ensemble learning, these feature sets are concatenated into different combinations. The best feature set is selected by Extremely Randomized Tree-Recursive Feature Elimination (ERT-RFE). The models are trained by Light eXtreme…
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Artikel Jurnal
Machine learning in medicine: a practical introduction
Abstract Background Following visible successes on a wide range of predictive tasks, machine learning techniques are attracting substantial interest from medical researchers and clinicians. We address the need for capacity development in this area by providing a conceptual introduction to machine…
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Artikel Jurnal
Explaining Machine Learning Solutions for Histopathology Images
Machine Learning may have huge benefits for the medical practice. The problem with accepting the machine learning solutions is that it is difficult for the medical staff to understand their decision and because of this they are not able to trust them as a helpful system for the day-to-day medical…
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Artikel Jurnal
Finding protein sites using machine learning methods
…nonsites that lack this role. 3. A single query site. A support vector machine classifier is built using feature vectors where each component represents a property in a given volume. Validation against an independent test set shows that this recognition approach has high sensitivity and…
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Artikel Jurnal Teks lengkap
Pullout Strength Predictor: A Machine Learning Approach
…feeling of insertion torque. The objective of the paper was to develop a machine learning based model using density of foam, insertion angle, insertion depth, and reinsertion to predict the pullout strength of pedicle screw. Methods To predict the pullout strength of pedicle screw, an experimental…
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Artikel Jurnal
Interpretable Machine Learning of Two‐Photon Absorption
…TPA database with ≈900 molecules, analyzing with interpretable machine learning (ML) the key molecular features explaining TPA magnitudes, and building a fast ML model for predictions. The ML model has prediction errors of similar magnitude compared to experimental and affordable QC methods errors…
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Artikel Jurnal
watex: machine learning research in water exploration
…for drilling operations, the prediction of flow rate, and the mixture learning strategy using machine learning are some sustainable solutions developed by watex to reduce the numerous losses for future hydro-geophysical engineering projects.
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Artikel Jurnal
Machine learning and its application in seismology
…However, there is also artificial intelligent computer technology, i.e. machine learning in the era of big data. The excellent capability of machine learning for implicit relation extraction and complex task processing has enabled it to be applied to a variety of fields. In this article, we…
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Artikel Jurnal
Machine Learning for Neuroimaging with Scikit-Learn
Statistical machine learning methods are increasingly used for neuroimaging data analysis. Their main virtue is their ability to model high-dimensional datasets, e.g. multivariate analysis of activation images or resting-state time series. Supervised learning is typically used in decoding or…
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Artikel Jurnal
Optimization of investment strategies through machine learning
The main objective of this research is to develop a sustainable stock quantitative investing model based on Machine Learning and Economic Value-Added techniques for optimizing investment strategies. Quantitative stock selection and algorithmic trading are the two features of the model. Principal…
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Artikel Jurnal
ONLINE NEWS CLASSIFICATION USING MACHINE LEARNING TECHNIQUES
…good collection of groups is significant and necessary. As the number of machine-readable documents proliferates, automatic text classification is badly needed to classify these documents. Unlabeled documents are categorized into predefined classes of labeled documents using text labeling, a…
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