The goal of this task is to build a binary classification model using Logistic Regression. The model is trained to predict a binary outcome (e.g., malignant vs benign tumors) using real-world data.

Learn what is Linear Regression Cost Function in Machine Learning and how it is used. Linear Regression Cost function in Machine Learning is "error" representation between actual value and model ...

Learn what is Logistic Regression Cost Function in Machine Learning and the interpretation behind it. Logistic Regression Cost function is "error" representation of the model. It shows how the model ...

Heart failure (HF) is a complex and varied condition that affects over 50 million people worldwide. Although there have been significant strides in understanding the underlying mechanisms of HF, ...

ABSTRACT: Road traffic accidents are one of the global safety and socioeconomic challenges. According to WHO (2024), it has caused over 1.19 million annual fatalities. It is also projected to cause ...

ABSTRACT: Over the past ten years, there has been an increase in cardiovascular disease, one of the most dangerous types of disease. However, cardiovascular detection is a technique that analyzes data ...

This project implements a Logistic Regression model trained using Stochastic Gradient Descent (SGD). The code includes functionality for training the model, evaluating its performance, and performing ...

Abstract: In the field of machine learning (ML) and big data analysis, sample data often needs to be classified. Traditional logistic regression can predict the sample set, and it is also the main ...