Sparse logistic regression (SLR), which is widely used for classification and feature selection in many fields, such as neural networks, deep learning, and bioinformatics, is the classical logistic ...

The paper bases on the theory of deep learning, uses the Scikit-learn machine learning framework and logistic regression algorithm, combines with supervised machine learning. Through Fourier transform ...

iPhone 18 Pro could finally make the iPhone look like an Android, with a single hole-punch camera and no visible Face ID sensors.

These insights could help scientists build models that are simpler, more efficient, and possibly more transparent. More information: Vittorio Erba et al, Bilinear Sequence Regression: A Model for ...

End-to-end machine learning project for predicting loan defaults on the HMEQ home equity loan dataset. Includes data preprocessing, EDA, feature engineering, model training (Logistic Regression, ...

A novel image encryption algorithm implementing 3D Logistic Map and Improved Chirikov Map for secure and robust image encryption. Features enhanced security through chaotic mapping, high key ...

The Philadelphia Phillies have relied on this budding star to anchor their rotation all season, but he appears to be regressing.

Study objective: In social epidemiology, it is easy to compute and interpret measures of variation in multilevel linear regression, but technical difficulties exist in the case of logistic regression.