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 early ...

Our Regularized Logistic Regression model showed an impressive 90% accuracy in predicting CVDs. The code was written in python using the Jupyter notebook environment.

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 ...

The Data Science Lab Logistic Regression from Scratch Using Raw Python The fundamental technique has been studied for decades, thus creating a huge amount of information and alternate variations that ...

Next, the demo trains a logistic regression model using raw Python, rather than by using a machine learning code library such as Microsoft ML.NET or scikit. [Click on image for larger view.] Figure 1: ...

Logistic Regression technique in machine learning both theory and code in Python. Includes topics from Assumptions, Multi Class Classifications, Regularization (l1 and l2), Weight of Evidence and ...

Brief about the loss function of logistic regression About L2 regularization Role of L2 regularization in Logistic Regression Implementing L2 regularization The penalty for failing to fulfil the ...