Tabular data: Deep learning is not all you need
R Shwartz-Ziv, A Armon - Information Fusion, 2022 - Elsevier
A key element in solving real-life data science problems is selecting the types of models to
use. Tree ensemble models (such as XGBoost) are usually recommended for classification …
use. Tree ensemble models (such as XGBoost) are usually recommended for classification …
Tabnet: Attentive interpretable tabular learning
We propose a novel high-performance and interpretable canonical deep tabular data
learning architecture, TabNet. TabNet uses sequential attention to choose which features to …
learning architecture, TabNet. TabNet uses sequential attention to choose which features to …
[HTML][HTML] Forecasting solar energy production in Spain: A comparison of univariate and multivariate models at the national level
T Cabello-López, M Carranza-García, JC Riquelme… - Applied Energy, 2023 - Elsevier
Renewable energies, such as solar power, offer a clean and cost-effective energy source.
However, their integration into national electricity grids poses challenges due to their …
However, their integration into national electricity grids poses challenges due to their …
[HTML][HTML] Classification of rice yield using UAV-based hyperspectral imagery and lodging feature
J Wang, B Wu, MV Kohnen, D Lin, C Yang… - Plant …, 2021 - spj.science.org
High-yield rice cultivation is an effective way to address the increasing food demand
worldwide. Correct classification of high-yield rice is a key step of breeding. However …
worldwide. Correct classification of high-yield rice is a key step of breeding. However …
GPU-accelerated CatBoost-forest for hyperspectral image classification via parallelized mRMR ensemble subspace feature selection
In this article, the graphics processing unit (GPU)-accelerated CatBoost (GPU-CatBoost)
algorithm for hyperspectral image classification is first introduced and comparatively studied …
algorithm for hyperspectral image classification is first introduced and comparatively studied …
Pavement aggregate shape classification based on extreme gradient boosting
Aggregate plays the role of skeleton filling in asphalt pavements. The shape of the
aggregate affects the embedded structure between the aggregates, thus affecting the …
aggregate affects the embedded structure between the aggregates, thus affecting the …
Integration of machine learning and hydrodynamic modeling to solve the extrapolation problem in flood depth estimation
Flood prediction is an important task, which helps local decision-makers in taking effective
measures to reduce damage to the people and economy. Currently, most studies use …
measures to reduce damage to the people and economy. Currently, most studies use …
A fog computing framework for intrusion detection of energy-based attacks on UAV-assisted smart farming
Precision agriculture and smart farming have received significant attention due to the
advancements made in remote sensing technology to support agricultural efficiency. In large …
advancements made in remote sensing technology to support agricultural efficiency. In large …
Tabular-to-Image Transformations for the Classification of Anonymous Network Traffic Using Deep Residual Networks
N Briner, D Cullen, J Halladay, D Miller… - IEEE …, 2023 - ieeexplore.ieee.org
With the meteoric rise in anonymous network traffic data, there is a considerable need for
effective automation in traffic identification tasks. Though many shallow and deep machine …
effective automation in traffic identification tasks. Though many shallow and deep machine …
[PDF][PDF] An end to end of scalable tree boosting system
Feature selection in the health sector is essential to do. Moreover, an analysis of which
variables are indeed important that affect specific diseases. In the 20th century, many …
variables are indeed important that affect specific diseases. In the 20th century, many …