204.674 hasil untuk machine learning
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Artikel Jurnal
Exploratory Analysis of Student Learning in a Thai Data Analytics and Machine Learning Course Using Machine Learning Techniques
This study examined patterns of student comprehension across core topics in a data analytics and machine learning course through a multi-method analytical approach. Data sources included student surveys, course learning outcome evaluations, examination performance. Data were analyzed using…
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Artikel Jurnal
Learning cell migration mechanisms using machine learning
…of cells as a whole. We present a new approach to take advantage of Machine Learning tools (Artificial Neural Networks) in order to predict the position and velocity of a cell in a certain moment in time, given the properties of said cell and the environment surrounding it. The results show a high…
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Artikel Jurnal
Enhancing adaptive learning with Moodle's machine learning
This review explores how Moodle's machine learning capabilities enhance adaptive learning. We analyze five studies using Moodle for predictive and prescriptive support in education. These studies cover topics like learner classification, early risk detection, predictor comparison, reliability…
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Artikel Jurnal Teks lengkap
Compact Data Learning for Machine Learning Classifications
This paper targets the area of optimizing machine learning (ML) training data by constructing compact data. The methods of optimizing ML training have improved and become a part of artificial intelligence (AI) system development. Compact data learning (CDL) is an alternative practical framework to…
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Artikel Jurnal
Roman Urdu sentiment analysis using Machine Learning with best parameters and comparative study of Machine Learning algorithms
…containing 21000 values with manually annotated and prepare the data for machine learning and then we apply different machine learning algorithms(SVM , Logistic regression , Random Forest, Naïve Bayes ,AdaBoost, KNN )(Bowers et al. 2018) with different parameters and kernels and with TFIDF(Unigram…
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Artikel Jurnal Teks lengkap
Machine Learning Assessment of Soil Carbon Sequestration Potential: Integrating Land Use, Pedology, and Machine Learning in Croatia
…a land-use-specific (LULC; Cropland, Forest land, Grassland) ensemble machine learning (ML) framework to quantify the soil carbon saturation deficit (SCSD) across Croatia’s pedologically diverse landscape on 622 soil samples. The LULC-stratified ensemble models (SVM, RF, CUB) achieved moderate to…
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Artikel Jurnal
Physically-constrained evapotranspiration models with machine learning parameterization outperform pure machine learning: Critical role of domain knowledge
Physics-informed machine learning techniques have emerged to tackle challenges inherent in pure machine learning (ML) approaches. One such technique, the hybrid approach, has been introduced to estimate terrestrial evapotranspiration (ET), a crucial variable linking water, energy, and carbon…
Juga tersedia di: DOAJ
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Artikel Jurnal
Simple rules outperform machine learning for personnel selection: insights from the 3rd annual SIOP machine learning competition
Abstract Machine learning (ML) algorithms are often assumed to be the most accurate way of producing predictive models despite problems with explainability and adverse impact. The 3rd annual Society for Industrial and Organizational Psychology Machine Learning Competition sought to find ML models…
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Artikel Jurnal
Comparing Scientific Machine Learning With Population Pharmacokinetic and Classical Machine Learning Approaches for Prediction of Drug Concentrations
ABSTRACT A variety of classical machine learning (ML) approaches has been developed over the past decade aiming to individualize drug dosages based on measured plasma concentrations. However, the interpretability of these models is challenging as they do not incorporate information on…
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Artikel Jurnal
Comparative Analysis of Automated Machine Learning and Optimized Conventional Machine Learning for Concrete’s Uniaxial Compressive Strength Prediction
…interacting factors. This study pioneers the application of automated machine learning (AutoML) and conventional ML techniques to unravel the intricate relationships between the UCS and six factors. A robust dataset comprising 844 experimental results was used to train and evaluate the models. The…
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Artikel Jurnal Teks lengkap
Machine Learning in Python: Main Developments and Technology Trends in Data Science, Machine Learning, and Artificial Intelligence
…it, from processing the massive piles of data generated each day to learning from and taking useful action. Deep neural networks, along with advancements in classical machine learning and scalable general-purpose graphics processing unit (GPU) computing, have become critical components of…
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Artikel Jurnal Teks lengkap
Reduced Data Volumes through Hybrid Machine Learning Compared to Conventional Machine Learning Demonstrated on Bearing Fault Classification
In some real-world problems, machine learning is faced with little data due to limited resources such as sensors, time, and budget. In this case, the conventional machine learning approach may fail or perform badly. To develop a well-functioning model with a small training set the hybrid machine…
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Artikel Jurnal
Supervised Learning in Physical Networks: From Machine Learning to Learning Machines
…Here we explore an alternative approach, namely physical coupled learning. In this paradigm, the system is not initially designed to accomplish a task, but physically adapts to applied forces to develop the ability to perform the task. Crucially, we require coupled learning to be facilitated by…
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Artikel Jurnal
Bridging the gap between Machine Learning and Medicine: Understanding recent advances in machine learning-based disease diagnosis systems.
…and complex datasets. Artificial Intelligence and recent advances in deep learning have become a vital aspect of our life and its positive results have been very astonishing. Medicine has been very receptive to the benefits of machine learning, as it adopts the rapidly evolving technology at a…
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Artikel Jurnal
Early Stage Machine Learning–Based Prediction of US County Vulnerability to the COVID-19 Pandemic: Machine Learning Approach
…geographical features. We developed a three-stage model using XGBoost, a machine learning algorithm, to quantify the probability of COVID-19 occurrence and estimate the number of potential occurrences for unaffected counties. Finally, these results were combined to predict the county-level risk…
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Artikel Jurnal Teks lengkap
Causal Machine Learning for Heterogeneous Cost Effects in Mutual Funds: A Double Machine Learning and Causal Forest Approach
…linear effect on returns. This study proposes an integrated causal machine learning framework to revisit this question using a panel of Hungarian open-ended public investment funds across all major asset classes—equity, bond, absolute yield, misc, money market, real estate, and commodity—covering…
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Artikel Jurnal
Forecasting Crude Oil Dynamics Using Multi-Frequency Machine Learning Approaches: Advanced Machine Learning Insights for Energy Market Stability
This study examines the forecasting of crude oil prices using a range of advanced machine learning techniques, including Support Vector Regression (SVR), AdaBoost, Gradient Boosting Regression (GBR), k-Nearest Neighbors (KNN), Neural Networks (NN), and Random Forest (RF), applied across daily…
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