Sep 9, 2022 · IgcForest first preserves the class distribution vectors of the main features by a pooling strategy to realise the feature reduction and reuse.
Sep 14, 2022 · An improved gcForest (IgcForest) classification algorithm from the perspective of memory reduction and weighting is proposed in this paper. ...
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Feb 7, 2024 · This paper proposes a novel forest-based ensemble algorithm called time series cascade forest (TSCF). TSCF integrates four base classifiers, ...
To solve these problems, an improved deep forest (IgcForest) classification algorithm is proposed in this paper. IgcForest first preserves the class ...
Sep 20, 2021 · Extremely randomized Trees(ET) is a powerful classification method developed by Geurts [37], which has been widely used in various prediction ...
This paper describes the procedures used by North Central Forest Experiment Station's Forest Inventory and Analysis Work Unit (NCFIA) in determining ...
A Neural Random Forest (NeuRF) and a Neural Deep Forest (NeuDF) as classification algorithms, which combine an ensemble of decision trees and neural ...
Sep 16, 2023 · This paper presents an optimized Deep Forest, featuring learnable, layerwise data augmentation policy schedules. Specifically, We introduce the ...
In this study, by empirically analyzing Kaggle diabetic retinal image data and combining the advantages of the original deep forest, the improved deep forest ...
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A Neural Random Forest (NeuRF) and a Neural Deep Forest (NeuDF) as classification algorithms, which combine an ensemble of decision trees and neural ...