Scientific Research Publishing

A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ()

A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ...
IEEE

Fuzzy LASSO Logistic Regression: A Regularized Framework for Interpretable Binary Classification Under Uncertainty

Abstract: Fuzzy classification models are important for handling uncertainty and heterogeneity in high-dimensional data. Although recent fuzzy logistic regression approaches have demonstrated ...
Hosted on MSN

Build logistic regression in Python from scratch easily

Implement Logistic Regression in Python from Scratch ! In this video, we will implement Logistic Regression in Python from Scratch. We will not use any build in models, but we will understand the code ...
Optics

Rice University algorithm interprets spectra more accurately

A project at Rice University has developed a new machine learning (ML) algorithm intended to improve the identification of biomarkers in optical spectra. As reported in ACS Nano, the algorithm could ...
IEEE

Beyond Traditional Methods: Utilizing Regularized Logistic Regression for Accurate Heart Disease Forecasting

Abstract: Cardiovascular diseases (CVDs), also known as ischemic heart diseases, are a major cause of deaths worldwide, accounting for about 16% of all fatalities. Our study focuses on predicting CVDs ...
Healthline

What Is Regression in Autism?

Autistic regression refers to a loss of previously acquired skills or a backtracking of developmental milestones. In young children, it may represent autism onset. In older children and adults, it may ...
Scientific Research Publishing

Niu, Z.H., Chen, B. and Bu, C.Y. (2022) Large Velocity Pulse Prediction and Influencing Factors Analysis Based on L1 Regularized Logistic Regression Model. Journal of ...

ABSTRACT: In view of the composition analysis and identification of ancient glass products, L1 regularization, K-Means cluster analysis, elbow rule and other methods were comprehensively used to build ...