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 ...

A machine learning project for binary classification of skin cancer as malignant or benign, utilizing models like XGBoost, LGBM Classifier, Adaboost, SVM, and Logistic Regression. Features ...

While multiple machine learning (ML) algorithms offered similar predictive performance, the cost-effective analysis revealed ...

Rigorous study design and analytical standards are required to generate reliable findings in healthcare from artificial intelligence (AI) research. One crucial but often overlooked aspect is the ...

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 ...

In this paper, we propose hierarchical clustering based logistic regression algorithm. It firstly selects multiple groups of features using random selection, and builds multiple models. After model ...

Master data science in 2025. Complete guide to machine learning, big data analytics, Python programming, statistical modeling, and AI-powered business intelligence.

Two separate Keras neural network architectures: A regression network for credit score prediction. A binary classification network for loan status. Threshold optimization for classification using ...