Create README.md
Browse files
README.md
ADDED
@@ -0,0 +1,25 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
---
|
2 |
+
library_name: sklearn
|
3 |
+
tags:
|
4 |
+
- tabular-regression
|
5 |
+
- materials property prediction
|
6 |
+
- baseline-trainer
|
7 |
+
---
|
8 |
+
|
9 |
+
**Model Description**
|
10 |
+
|
11 |
+
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.
|
12 |
+
It predicts the Tc value using the chemical composition as a feature.
|
13 |
+
E.g: To predict the Tc value Nd2Fe14B1 magnet composition, the features are Nd=2, Fe=14, and B=1.
|
14 |
+
|
15 |
+
|
16 |
+
**Application & Limitations**
|
17 |
+
|
18 |
+
The trained model is valid for 14:2:1 phases only, which are stoichiometric compositions.
|
19 |
+
|
20 |
+
**Model Plot**
|
21 |
+
|
22 |
+
**How to use the trained model for inference**
|
23 |
+
|
24 |
+
|
25 |
+
|