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Found 4 papers, 1 papers with code
Morphological Classification of Extragalactic Radio Sources Using Gradient Boosting Methods
Most recent contributions in the field of morphological classification of extragalactic radio sources have proposed classifiers based on convolutional neural networks.
Martian Ionosphere Electron Density Prediction Using Bagged Trees
Furthermore, the optimized bagged regression trees model outperformed other Martian ionosphere models from the literature (MIRI and NeMars) in finding the peak electron density value, and the peak density height in terms of root-mean-square error and mean absolute error.
Amplitude Scintillation Forecasting Using Bagged Trees
Electron density irregularities present within the ionosphere induce significant fluctuations in global navigation satellite system (GNSS) signals.
Empirical evaluation of shallow and deep learning classifiers for Arabic sentiment analysis
Additionally, the comparison includes state-of-the-art models such as the transformer architecture and the araBERT pre-trained model.
