Machine learningEducational data miningIn this paper education support methods utilizing information technology in the university are examined. We propose prediction models in learning analytics using the student teaching data and examine the effectiveness of machine learning methods. Some examples of ...
"Our successful prediction not only underscores the significance of strengthening Antarctic sea ice prediction research but also demonstrates the substantial application potential of deep learning methods in this critical area," said Yang Qinghua, a professor of Sun Yat-sen University.■...
We used machine learning algorithms such as logistic regression, k-nearest neighbor (KNN), boosting, decision tree (DT), random forest (RF) and bagging to design prediction models for patient no-show in online outpatient appointments. The patient no-show rate of online outpatient appointment was...
This ensures the model is trained on well-organized, clean data, mitigating overfitting and enriching interpretability for machine learning algorithms. Source: Unsplash Model training In the subsequent step, model training implicates constructing a robust model using methods like boosting. This phase is ...
Machine Learning and Semantic Sentiment Analysis based Algorithms for Suicide Sentiment Prediction in Social Networks We then propose, for a better analysis, to investigate Weka as a tool of data mining based on machine learning algorithms that can extract useful information from Twitter data collected...
Statistical and now machine learning prediction methods have been gaining popularity in the field of landslide susceptibility modeling. Particularly, these data driven approaches show promise when tackling the challenge of mapping landslide prone areas for large regions, which may not have sufficient geotec...
It has been demonstrated that the data obtained by these methods is often incomplete and suffers from high false-positive and false-negative rates. In order to deal with this technology-driven problem, several machine learning techniques have been employed in the past to improve the accuracy and ...
Gu MY, Chen YL (2019) Two improvements of similarity-based residual life prediction methods. J Intell Manuf 30:303–315. https://doi.org/10.1007/s10845-016-1249-3 Article Google Scholar Mitchell TM (1997) Machine Learning, 1st edn. McGraw-Hill Inc, New York MATH Google Scholar Coble...
There is increasing interest in machine learning-based prediction models in inflammatory bowel diseases [IBD]. We synthesised and critically appraised studies comparing machine learning vs traditional statistical models, using routinely available clinical data for risk prediction in IBD. METHODS. Through a...
With the continuous development of machine learning, machine learning methods have been widely used in runoff predictions because of their excellent performance and relatively high applicability. For instance, the Artificial Neural network model and Long Short-Term Memory network model were applied to sim...