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With the rise of 3D printing and other advanced manufacturing methods, engineers can now build structures that were once ...
The XGBoost algorithm classifies network traffic flow that violates a set threshold into normal or abnormal traffic. We evaluated the performance of our scheme using CICDDoS2019, NSL-KDD, and CAIDA ...
3. Leaf-Wise Tree Growth: Unlike traditional gradient boosting, which uses a level-wise approach, LightGBM employs a leaf-wise tree growth strategy. This method expands the leaf with the greatest ...
Gradient Boosting Decision Trees regression, dichotomy and multi-classification are realized based on python, and the details of algorithm flow are displayed, interpreted and visualized to help ...
Each new tree in boosting is a fit to a modified copy of the original dataset. Boosting can be explained as a numerical optimization problem that the objective is to minimize the loss function defined ...
We show empirically that our method preserves the accuracy of gradient boosting while improving widely used group and individual fairness metrics. This work aims to train an ML model that is ...
Accurate bus passenger flow prediction contributes to informed decisions and full utilization of transit supply. Passenger flow is affected by an extensive range of attributes featuring travel ...
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