Αποτελέσματα Αναζήτησης
8 Οκτ 2018 · This study opens the door to deep learning based on non-differentiable modules without gradient-based adjustment, and exhibits the possibility of constructing deep models without backpropagation. deep forest, deep learning, machine learning, ensemble methods, decision trees.
1 Φεβ 2021 · DF21 is an implementation of Deep Forest 2021.2.1. It is designed to have the following advantages: Powerful: Better accuracy than existing tree-based ensemble methods. Easy to Use: Less efforts on tunning parameters. Efficient: Fast training speed and high efficiency. Scalable: Capable of handling large-scale data.
14 Ιουν 2022 · Nowadays, diversity is the holy grail of model accuracy: deep forest is a promising framework based on deep learning layers but without neurons and back propagation. The revolutionary deep...
1 Ιαν 2019 · This study opens the door to deep learning based on non-differentiable modules without gradient-based adjustment, and exhibits the possibility of constructing deep models without...
28 Φεβ 2017 · This study opens the door to deep learning based on non-differentiable modules without gradient-based adjustment, and exhibits the possibility of constructing deep models without backpropagation.
1 Φεβ 2021 · Easy to Use: Less efforts on tunning parameters. Efficient: Fast training speed and high efficiency. Scalable: Capable of handling large-scale data. DF21 offers an effective & powerful option to the tree-based machine learning algorithms such as Random Forest or GBDT.
28 Φεβ 2017 · The deep forest model, a random forest (RF) ensemble approach and an alternative to Deep Neural Network (DNN), has performance highly competitive to DNN in many classification tasks.
