library_name: sklearn
tags:
- tabular-regression
- machine-learning
- civil-engineering
datasets:
- custom
license: mit
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.