Unlike conventional gradient-based methods, which suffer from vanishing gradients and inefficient training, our proposed approach can effectively minimize squared loss and logistic loss. To make ALS ...

Different studies were focused on the determinants of complementary feeding and inadequate MAD among 6–23-month-old children using classical models such as binary and multilevel logistic regression ..

While regression models are suitable for these learning tasks, these labels are often discretized into binary classes to formulate the problem as a conventional classification task (e.g., classes with ...

the fault diagnosis model of the equipment is established from the bottom up through data level fusion (data association fusion), feature level fusion (preliminary diagnosis of multi-classification ...

The models are built using 30 real-valued features from 569 instances in the dataset. GridSearchCV was used for Logistic Regression, SVM, and the Ensemble model, optimizing for ROC AUC. Tuning was ...

Custom implementations of classification algorithms, including k-nearest neighbors for binary and multi-class problems, a perceptron for binary classification, and a one-vs-rest strategy for extending ...