CORAL and CORN implementations for ordinal regression with deep neural networks.

Ordinal Regression and Classification Algorithms

Tensorflow Keras implementation of ordinal regression using consistent rank logits (CORAL) by Cao et al. (2019)

Open-source Python toolkit focused on deep learning with ordinal methodologies

43th place (top2%) Solution for Kaggle APTOS 2019 Blindness Detection

Repository of the COLING 2022 paper : Ordinal Log-Loss - A simple log-based loss function for ordinal text classification.

A package to build Gradient boosted trees for ordinal labels

[ECCV 2024] Teach CLIP to Develop a Number Sense for Ordinal Regression

[WACV 2024] Official PyTorch implementation of: Ordinal Classification with Distance Regularization for Robust Brain Age Prediction

Official Code of AAAI 2023 paper "Controlling Class Layout for Deep Ordinal Classification via Constrained Proxies Learning".

Classifying classes with ordinality

parsnip bindings for ordinal prediction models

A list of ordinal datasets publicly available

Ordinal Losses for Classification of Cervical Cancer Risk

Implementation of the Class Distance Weighted Cross-Entropy Loss in PyTorch.

A data science project to predict online pet adoption speed using image, natural language, and tabular data with a multi-modal ML framework.

Code for the paper `Non-parametric Uni-modality Constraints for Deep Ordinal Classification`.

A Multimodal Deep Learning framework for early ICU outcome prediction (Length of Stay and Mortality) on MIMIC-III. Features bi-LSTM vital-sign encoding, an MLP for clinical + lab data, 8-head Cross-Modal Attention Fusion, Platt temperature scaling calibration, and an interactive Streamlit clinical decision support dashboard.

Transformer-based modeling of hotel review text to predict star ratings (1–5), evaluate ordinal classification performance, and analyze sentiment separability through embedding-based clustering.

Multivariate analysis (MVA) of high dimensional heterogeneous data