Results 41 to 50 of about 839,459 (306)
Interpreting uninterpretable predictors: kernel methods, Shtarkov solutions, and random forests
Statistical Theory and Related Fields, 2022 Many of the best predictors for complex problems are typically regarded as hard to interpret physically. These include kernel methods, Shtarkov solutions, and random forests.
T. M. Le, Bertrand Clarke
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Optimasi Prakiraan Cuaca Menggunakan Metode Ensemble pada Naïve Bayes dan C4.5
JuTISI (Jurnal Teknik Informatika dan Sistem Informasi), 2022 Peramalan cuaca merupakan hal yang penting bagi keberlangsungan hidup masyarakat luas. Oleh karena itu, akurasi dari peramalan cuaca haruslah tinggi. Berdasarkan hal itu maka dilakukan penelitian untuk meningkatkan akurasi peramalan cuaca dengan model ...
Vini Indri Yani +2 more
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Boosting methods for multi-class imbalanced data classification: an experimental review
Journal of Big Data, 2020 Since canonical machine learning algorithms assume that the dataset has equal number of samples in each class, binary classification became a very challenging task to discriminate the minority class samples efficiently in imbalanced datasets.
J. Tanha +4 more
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Comparison of Ensemble Machine Learning Methods for Soil Erosion Pin Measurements
ISPRS International Journal of Geo-Information, 2021 Although machine learning has been extensively used in various fields, it has only recently been applied to soil erosion pin modeling. To improve upon previous methods of quantifying soil erosion based on erosion pin measurements, this study explored the
Kieu Anh Nguyen +3 more
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Machine Learning-Based Forecasting of Bitcoin Price Movements
Proceedings of the International Conference on Applied Innovations in ITIn the volatile realm of cryptocurrency markets, this research explores the intricate dance of Bitcoin price dynamics through the lens of machine learning. Employing a multifaceted approach, we harness the power of Long Short-Term Memory (LSTM) networks,
Darko Angelovski +4 more
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Sensors, 2022 Software products from all vendors have vulnerabilities that can cause a security concern. Malware is used as a prime exploitation tool to exploit these vulnerabilities.
Rajesh Kumar, Geetha Subbiah
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Foundations and Innovations in Data Fusion and Ensemble Learning for Effective Consensus
MathematicsEnsemble learning and data fusion techniques play a crucial role in modern machine learning, enhancing predictive performance, robustness, and generalization.
Ke-Lin Du +4 more
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PREDICTION OF SOFTWARE ANOMALIES METHODS BASED ON ENSEMBLE LEARNING METHODS
Mağallaẗ Al-kūfaẗ Al-handasiyyaẗSoftware plays a vital role in all aspects of our daily lives, specifically in the fields of medicine and industry. In order to design high-quality and reliable software and avoid risks resulting from software errors, including physical and human errors,
Raghda Azad Hasan, Ibrahim Ahmed Saleh
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Boosting Few-Shot Visual Learning With Self-Supervision [PDF]
IEEE International Conference on Computer Vision, 2019 Few-shot learning and self-supervised learning address different facets of the same problem: how to train a model with little or no labeled data. Few-shot learning aims for optimization methods and models that can learn efficiently to recognize patterns ...
Spyros Gidaris +4 more
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Diagnosis of Diabetes Mellitus Using Gradient Boosting Machine (LightGBM)
Diagnostics, 2021 Diabetes mellitus (DM) is a severe chronic disease that affects human health and has a high prevalence worldwide. Research has shown that half of the diabetic people throughout the world are unaware that they have DM and its complications are increasing,
Derara Duba Rufo +3 more
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