Recent advances in decision trees: An updated survey
VG Costa, CE Pedreira - Artificial Intelligence Review, 2023 - Springer
Abstract Decision Trees (DTs) are predictive models in supervised learning, known not only
for their unquestionable utility in a wide range of applications but also for their interpretability …
for their unquestionable utility in a wide range of applications but also for their interpretability …
Machine learning in aerodynamic shape optimization
Abstract Machine learning (ML) has been increasingly used to aid aerodynamic shape
optimization (ASO), thanks to the availability of aerodynamic data and continued …
optimization (ASO), thanks to the availability of aerodynamic data and continued …
What matters in the e-commerce era? Modelling and mapping shop rents in Guangzhou, China
The rise of e-commerce is changing consumer behaviours and the value of retail space.
Tracking the changes of shop rents under the impact of e-commerce and understanding the …
Tracking the changes of shop rents under the impact of e-commerce and understanding the …
Multi-class confusion matrix reduction method and its application on net promoter score classification problem
The paper presents a novel method for reducing a multi-class Confusion Matrix into a 2× 2
version enabling the use of the relevant performance metrics and methods like the Receiver …
version enabling the use of the relevant performance metrics and methods like the Receiver …
Towards understanding ensemble, knowledge distillation and self-distillation in deep learning
Z Allen-Zhu, Y Li - arXiv preprint arXiv:2012.09816, 2020 - arxiv.org
We formally study how ensemble of deep learning models can improve test accuracy, and
how the superior performance of ensemble can be distilled into a single model using …
how the superior performance of ensemble can be distilled into a single model using …
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
In the last few years, Artificial Intelligence (AI) has achieved a notable momentum that, if
harnessed appropriately, may deliver the best of expectations over many application sectors …
harnessed appropriately, may deliver the best of expectations over many application sectors …
A practical tutorial on bagging and boosting based ensembles for machine learning: Algorithms, software tools, performance study, practical perspectives and …
Ensembles, especially ensembles of decision trees, are one of the most popular and
successful techniques in machine learning. Recently, the number of ensemble-based …
successful techniques in machine learning. Recently, the number of ensemble-based …
Eigen-cam: Class activation map using principal components
MB Muhammad, M Yeasin - 2020 international joint conference …, 2020 - ieeexplore.ieee.org
Deep neural networks are ubiquitous due to the ease of developing models and their
influence on other domains. At the heart of this progress is convolutional neural networks …
influence on other domains. At the heart of this progress is convolutional neural networks …
Simulated annealing-based dynamic step shuffled frog leaping algorithm: Optimal performance design and feature selection
The shuffled frog leaping algorithm is a new optimization algorithm proposed to solve the
combinatorial optimization problem, which effectively combines the memetic algorithm …
combinatorial optimization problem, which effectively combines the memetic algorithm …
Data‐driven materials science: status, challenges, and perspectives
Data‐driven science is heralded as a new paradigm in materials science. In this field, data is
the new resource, and knowledge is extracted from materials datasets that are too big or …
the new resource, and knowledge is extracted from materials datasets that are too big or …