2021315 · This data availability in great sizes and the increasing quantity draw attention to study in machine learning concept. Machine learning (ML) and data mining (DM) applications came to existence in this sector nearly two …
view more202093 · Then we analyze the basic process of data mining, summary several major machine learning algorithms, and put forward the challenges faced by machine learning algorithms in the mining of biological sequence data and possible solutions in the future.
view more2022825 · Crop yield and its prediction are crucial in agricultural production planning. This study investigates and predicts arabica coffee yield in order to match the market demand, using artificial ...
view more2016129 · Data Mining: Practical Machine Learning Tools and Techniques offers a thorough grounding in machine learning concepts as well as practical advice on applying the tools and techniques in real-world data mining situations. This highly anticipated fourth edition of the most acclaimed work on data mining and machine learning will teach you …
view more202233 · Educational data mining has become an effective tool for exploring the hidden relationships in educational data and predicting students' academic achievements. This study proposes a new model based on machine learning algorithms to predict the final exam grades of undergraduate students, taking their midterm exam grades as the source …
view moreMing Yin, Jennifer Wortman Vaughan, and Hanna Wallach. 2019. Understanding the effect of accuracy on trust in machine learning models. In Conference on Human Factors in Computing Systems - Proceedings. Association for Computing Machinery. Digital Library Google Scholar [31]
view more2024316 · It is critical to quantify both the progress the GDPR has made toward improving privacy policies, and the remaining work to be done in those policies to fulfill the promise of the GDPR in ...
view more202071 · The development of data mining, knowledge discovery, and machine learning that refers creating algorithms and program which learn on their own, together with the original data analysis and descriptive analytics from the statistical perspective, forms the general concept of “data analytics” [ 47 ].
view more202411 · Additionally, the machine learning component of our approach could be improved by using more sophisticated GB local atomic environment descriptors and techniques like active learning to achieve accurate prediction of finite temperature segregation with fewer TI simulations.
view more1 · Data mining is the use of machine learning and statistical analysis to uncover patterns and other valuable information from large data sets.
view moreBased on over 30 years' experiences in design, production and service of crushing and s
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