The results indicate that the machine learning algorithms outperform the drainage area ratio and spatial proximity transfer methods. Among machine learning algorithms, random forests obtain lower (better) continuous ranked probability scores than the other methods for 10 out of 11 test basins.doi:10.1080/02626667.2023.2273402Shahriar M...
Evaluation of deep learning algorithms for national scale landslide susceptibility mapping of Iran[J]. Geoscience Frontiers, 2021, 12(2): 505-519. DOI: 10.1016/j.gsf.2020.06.013 [10] Yacine Achour, Hamid Reza Pourghasemi. How do machine learning techniques help in increasing accuracy of ...
assessment of surgical skills is a manual and time-consuming process which is prone to subjective interpretation. This study aims to automate surgical skill assessment in laparoscopic cholecystectomy videos using machine learning algorithms. To address this, a three-stage machine learning method is propos...
This dataset definitely brings out the slowness of a number of machine learning algorithms. The 2009 KDD Challenge small dataset is definitely lower dimensional than the large dataset but is still characterized by a considerable number of columns: 230 input features and three possible target features...
Although deep learning algorithms for point clouds have attracted much attention, the methods have not been widely used in plant phenotype processing. This could be because plant point clouds are more complex than buildings, furniture, etc., and there are few open source datasets. Besides, various...
The non-existence of the uniform first integral of triple system reveals the impossibility of finding closed-form analytic solutions of three-body problems in general cases: it clearly indicates that we mostly had to (i.e. must) use numerical algorithms to solve this problem. This was indeed ...
It is therefore unsurprising that the machine learning algorithms also struggle when confronted with the challenge of finding a rare feature in the dataset. 5. Discussion In this study, continuing with the paradigm in and improving upon the results of [1], [2], we utilise neural networks and...
All computational algorithms utilized in the manuscript have been referenced in the corresponding figure legend and described in the methods section. Additional details can be made available upon request. References Polyak, K., Haviv, I. & Campbell, I. G. Co-evolution of tumor cells and their ...
Section 3.1 we describe a general decision-theoretic approach (that can be seen as a generalization of the standard three-way decision-theoretic framework), while in Sections 3.2 and 3.4 we present algorithm-tailored techniques that are obtained by modifications of standard Machine Learning algorithms...
In addition, machine learning algorithms have been rapidly developed during the past decades, which can be roughly classified into two branches, i.e., supervised learning algorithms and unsupervised learning algorithms [31]. In specific, supervised learning algorithms mainly include linear regression, lo...