By modeling the single-trial electroencephalogram of participants performing perceptual decisions, and building on predictions from two century-old psychological laws, we estimate the times of ...
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports ...
In the swiftly evolving tech landscape, Artificial Intelligence (AI) and Machine Learning (ML) have emerged as two of the most ...
ABSTRACT: This paper investigates the application of machine learning techniques to optimize complex spray-drying operations in manufacturing environments. Using a mixed-methods approach that combines ...
The ML Algorithm Selector is an interactive desktop application built with Python and Tkinter. It guides users through a decision-making process to identify suitable machine learning algorithms for ...
ABSTRACT: Decision tree is an effective supervised learning method for solving classification and regression problems. This article combines the Pearson correlation coefficient with the CART decision ...
Introduction: The study aims to predict tooth extraction decision based on four machine learning methods and analyze the feature contribution, so as to shed light on the important basis for experts of ...
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