Results 31 to 40 of about 370,101 (314)

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, Aradea Aradea, Husni Mubarok   +2 more
doaj   +1 more source

Domain Transfer Multiple Kernel Boosting for Classification of EEG Motor Imagery Signals

IEEE Access, 2019
The application of wireless sensors in the brain-computer interface (BCI) system provides great convenience for the acquisition of electroencephalography (EEG) signals.
Mengxi Dai, Shuai Wang, Dezhi Zheng, Rui Na, Shuailei Zhang   +4 more
doaj   +1 more source

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
doaj   +1 more source

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, Walter Chen, Bor-Shiun Lin, Uma Seeboonruang   +3 more
doaj   +1 more source

Combining Quadratic Penalization and Variable Selection via Forward Boosting [PDF]

, 2011
Quadratic penalties can be used to incorporate external knowledge about the association structure among regressors. Unfortunately, they do not enforce single estimated regression coefficients to equal zero.
Tutz, Gerhard, Ulbricht, Jan
core   +1 more source

Zero-Day Malware Detection and Effective Malware Analysis Using Shapley Ensemble Boosting and Bagging Approach

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
doaj   +1 more source

Smoothing with Curvature Constraints based on Boosting Techniques [PDF]

, 2006
In many applications it is known that the underlying smooth function is constrained to have a specific form. In the present paper, we propose an estimation method based on the regression spline approach, which allows to include concavity or convexity ...
Gerhard Tutz, Leitenstorfer, Florian, Tutz, Gerhard, Florian Leitenstorfer   +3 more
core   +1 more source

Machine Learning-Based Forecasting of Bitcoin Price Movements

Proceedings of the International Conference on Applied Innovations in IT
In 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, Bojana Velichkovska, Goran Jakimovski, Danijela Efnusheva, Marija Kalendar   +4 more
doaj   +1 more source

Boosting Nonlinear Additive Autoregressive Time Series [PDF]

, 2007
Within the last years several methods for the analysis of nonlinear autoregressive time series have been proposed. As in linear autoregressive models main problems are model identification, estimation and prediction.
Tutz, Gerhard, Shafik, Nivien
core   +1 more source

Foundations and Innovations in Data Fusion and Ensemble Learning for Effective Consensus

Mathematics
Ensemble learning and data fusion techniques play a crucial role in modern machine learning, enhancing predictive performance, robustness, and generalization.
Ke-Lin Du, Rengong Zhang, Bingchun Jiang, Jie Zeng, Jiabin Lu   +4 more
doaj   +1 more source