You could sift through websites, but some Python code and a little linear regression could make the job easier. ...

This paper introduces a new instance-based algorithm for multiclass classification problems where the classes have a natural order. The proposed algorithm extends the state-of-the-art gravitational ...

With excellent representation power for complex data, deep neural networks (DNNs) based approaches are state-of-the-art for ordinal regression problem which aims to classify instances into ordinal ...

This repository is provided as a tutorial for the implementation of integration algorithms of first and second order ODEs through recurrent neural networks in Python. The first order example ...

Includes data preprocessing, EDA, feature engineering, model training (Logistic Regression, Random Forest, XGBoost), hyperparameter tuning, model comparison, SHAP-based interpretability, and business ...

TITLE: Ordinal Logistic Regression Model in Determining Factors Associated with Household Food Insecurity in Namibia AUTHORS: Dibaba B. Gemechu, Leonard O. M. Elifas KEYWORDS: Food Insecurity, Ordinal ...

Lelisho, M.E., Wogi, A.A. and Tareke, S.A. (2022) Ordinal Logistic Regression Analysis in Determining Factors Associated with Socioeconomic Status of Household in Tepi Town, Southwest Ethiopia. The ...