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c3cf
kycai23/c3cf
c3cf is a tabular regression model from kycai23. Use it for the tabular regression task on the model card, and read the license before you ship it in a product. It is set up for sklearn. The card lists the license as mit.
c3cf, Cascade Forest models for predicting the Compressive strength of Coal-ash-incorporated Cement composites, were developed in the research article: Coal ashes as supplementary cementitious materials: physicochemic…
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Public
Updated Aug 15, 2026
Repo size
1.3 GB
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1
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Repo makeup
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.pkl1.3 GB · 100%
At a glance
- Task
- Tabular Regression
- Library
- sklearn
- License
- mit
- Model type
- cascade_forest
- Access
- Public
- Created
- Dec 31, 2025
- Updated
- Aug 15, 2026
- SHA
- fe9f2b26
Datasets
Model card
From the Hugging Face model README
Model Name: c3cf
Model Description
c3cf, Cascade Forest models for predicting the Compressive strength of Coal-ash-incorporated Cement composites, were developed in the research article: Coal ashes as supplementary cementitious materials: physicochemical property effects on hydration and strength, along with property-informed machine learning modeling. They are tree-based ensemble models that implements the deep forest algorithm.
- Developed by: Kangyi Cai @ Missouri S&T
- Model type: Cascade Forest
- Language(s): Python
- License: MIT
Uses & Limitations
c3cf can make reasonable predictions for coal-ash-incorporated cement mortars, whose strength is in the range of 15-65 MPa, replacement level of coal ash is <50% by mass, and curing age is between 7 and 91 days.
How to Get Started with the Model
This repository contains a collection of regression models located in the regs/ directory. Refer to the kycai/c3cf for detailed guides.
from huggingface_hub import snapshot_download
path = snapshot_download(repo_id="kycai23/c3cf")
Training & Evaluation
Refer to the research article mentioned above.
- Task
- Tabular Regression
- Library
- sklearn
- Type
- cascade_forest
- License
- mit
- Created
- Dec 31, 2025
- Updated
- Aug 15, 2026