---
library_name: sklearn
tags:
- tabular-regression
- materials property prediction
- baseline-trainer
---

**Model Description**

The magnet Curie temperature (Tc [K]) predictor model has been trained using a supervised learning approach on a specific set of magnet classes having 14:2:1 phases.
It predicts the Tc value using the chemical composition as a feature.
E.g: To predict the Tc value Nd2Fe14B1 magnet composition, the features are Nd=2, Fe=14, and B=1.


**Application & Limitations**

The trained model is valid for 14:2:1 phases only, which are stoichiometric compositions.

**Model Plot**

**How to use the trained model for inference**