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 ...

In forecasting economic time series, statistical models often need to be complemented with a process to impose various constraints in a smooth manner. Systematically imposing constraints and retaining ...

JSON Prompting is a technique for structuring instructions to AI models using the JavaScript Object Notation (JSON) format, making prompts clear, explicit, and machine-readable. Unlike traditional ...

Multiplication in Python may seem simple at first—just use the * operator—but it actually covers far more than just numbers. You can use * to multiply integers and floats, repeat strings and lists, or ...

When using multinomial logistic regression with warm starts from a previous iteration, the final coefficients in the model are correct, but the intercepts somehow get filled with incorrect numbers ...

1 Clinical Laboratory, Dongyang People’s Hospital, Dongyang, Zhejiang, China 2 Clinical Laboratory, The Second People’s Hospital of Yuhuan City, Yuhuan, Zhejiang, China Introduction: In this study, we ...

ABSTRACT: Introduction: Biopsy procedures represent an essential diagnostic tool in the management of oral lesions. This study aims to evaluate the knowledge, attitudes, and practices of dental ...

Background: Arthritis is the most disabling disease worldwide, and the presence of the disease usually greatly threatens the patient’s activities of daily living (ADL). Currently, there are a few ...

Abstract: This study combined linear discriminant analysis (LDA) and multivariate logistic regression models to systematically analyze key indicators in flood prediction, aiming to identify factors ...

Logistic Regression is a widely used model in Machine Learning. It is used in binary classification, where output variable can only take binary values. Some real world examples where Logistic ...