Titlebook: Recent Advances in Soft Computing and Data Mining; Proceedings of the F Rozaida Ghazali,Nazri Mohd Nawi,Nureize Arbaiy Conference proceedin

Gudgeon

小平面

2367-3370 oblem with the most efficient tools and techniques. To thrive in these data-driven ecosystems, researchers, data analysts, and practitioners must understand the design choice and options of these approaches978-3-031-00830-6978-3-031-00828-3Series ISSN 2367-3370 Series E-ISSN 2367-3389

倔強不能

PSS: New Parametric Based Clustering for Data Categorys, purity and rand index using benchmarks datasets. The experiment results show that the proposed approach has improved the processing times up to 92.96%. It also has better performance in term of purity and rand index and error mean of the estimation parameters.

avarice

Fuzzy-Autoregressive Integrated Moving Average (F-ARIMA) Model to Improve Temperature Forecastzzy triangles for managing fuzzy data. The proposed method for creating fuzzy numbers using standard deviations yields fewer prediction errors and increases model performance, according to the experimental results. This is because data errors have been rectified, and model development errors have be

Platelet

Friendship Prediction in Social Networks Using Developed Extreme Learning Machine with Kernel Reductto the capability of achieving absolute accuracy with less number of features. Experimental results showed the superiority of ILP-PRKELM with an accomplished accuracy of 84.6 and 78.6 for Last.fm and Douban respectively, which is equivalent to 2% improved accuracy over the benchmarks.

inquisitive

Spinal-Fusion

Prediction of ADHD from a Small Dataset Using an Adaptive EEG Theta/Beta Ratio and PCA Feature Extraen subject analyses, with accuracy getting worse with the increase of EEG segments. The contribution of this work is two-fold: the practical application allows for a reliable adoption of machine learning in non-invasive EEG screening of small ADHD dataset, while the theoretical contribution extends