How-To Geek on MSN

Generate realistic test data in Python fast. No dataset required

Learn the NumPy trick for generating synthetic data that actually behaves like real data.
IEEE

Influence-Balanced XGBoost: Improving XGBoost for Imbalanced Data Using Influence Functions

Abstract: Decision tree boosting algorithms, such as XGBoost, have demonstrated superior predictive performance on tabular data for supervised learning compared to neural networks. However, recent ...
Dot Physics on MSN

Compute and visualize electric fields with Python | Two charges

In this video, we compute and visualize the electric field from two charges using Python, showing how to calculate field vectors and plot the results clearly. Perfect for learning electrostatics, ...
IEEE

Using Radial Basis Function Neural Network With Weight Memory Mechanism: Nonlinear System Identification

Abstract: The radial basis function neural network (RBFNN) is a learning model with better generalization ability, which attracts much attention in nonlinear system identification. Compared with the ...