Heat capacity @ 25K - meV/atom - Cv_25#
ARFS Top features#
ARFS selected descriptors#
Correlation analysis#
Distance correlation#
Dependency graphs#
Feature learnability#
Model performance#
5-Fold CV Metrics overview#
RF - MATMINER
train_rmse |
test_rmse |
train_errors |
test_errors |
train_r2 |
test_r2 |
|
|---|---|---|---|---|---|---|
mean |
0.00254 |
0.00684 |
0.00168 |
0.00466 |
0.992 |
0.94062 |
min |
0.0024 |
0.006 |
0.0016 |
0.0043 |
0.9917 |
0.924 |
max |
0.0026 |
0.0073 |
0.0017 |
0.0051 |
0.9923 |
0.9561 |
std |
8e-05 |
0.000440908 |
4e-05 |
0.000272764 |
0.0002 |
0.0106304 |
RF - MATMINER+LOBSTER
train_rmse |
test_rmse |
train_errors |
test_errors |
train_r2 |
test_r2 |
|
|---|---|---|---|---|---|---|
mean |
0.0025 |
0.0068 |
0.00168 |
0.00462 |
0.99204 |
0.94168 |
min |
0.0025 |
0.0059 |
0.0016 |
0.0042 |
0.9918 |
0.93 |
max |
0.0025 |
0.0072 |
0.0017 |
0.005 |
0.9922 |
0.9577 |
std |
0 |
0.000460435 |
4e-05 |
0.000271293 |
0.000162481 |
0.00922115 |
MODNet - MATMINER
train_rmse |
test_rmse |
train_errors |
test_errors |
train_r2 |
test_r2 |
|
|---|---|---|---|---|---|---|
mean |
0.00438 |
0.00552 |
0.00298 |
0.00376 |
0.9757 |
0.96168 |
min |
0.0039 |
0.005 |
0.0027 |
0.0036 |
0.9709 |
0.9525 |
max |
0.0048 |
0.0058 |
0.0033 |
0.0039 |
0.9813 |
0.9671 |
std |
0.000305941 |
0.000278568 |
0.000203961 |
0.00010198 |
0.00358664 |
0.00508268 |
MODNet - MATMINER+LOBSTER
train_rmse |
test_rmse |
train_errors |
test_errors |
train_r2 |
test_r2 |
|
|---|---|---|---|---|---|---|
mean |
0.00414 |
0.00564 |
0.00292 |
0.00386 |
0.97822 |
0.95962 |
min |
0.0038 |
0.0049 |
0.0026 |
0.0034 |
0.9665 |
0.9501 |
max |
0.0052 |
0.0065 |
0.0037 |
0.0044 |
0.9823 |
0.9705 |
std |
0.000535164 |
0.000535164 |
0.000396989 |
0.00032 |
0.00589827 |
0.00840795 |
Corrected resampled t-test on 10-fold CV#
Summary
t_stat |
p_value |
significance_stars |
d_av |
rel_improvement |
percent_folds_improved |
|
|---|---|---|---|---|---|---|
RF |
1.23233 |
0.124525 |
0.195034 |
1.80666 |
80 |
|
MODNet |
-1.26104 |
0.880499 |
-0.411092 |
-2.9137 |
20 |
Model Explainer#
PFI#
SHAP#
Misc#
ARFS#
n-iter convergence checks
LightGBM - MATMINER+LOBSTER
train_rmse |
test_rmse |
train_errors |
test_errors |
train_r2 |
test_r2 |
|
|---|---|---|---|---|---|---|
mean |
0.00290039 |
0.00629052 |
0.000938621 |
0.00399273 |
0.989348 |
0.949987 |
min |
0.00249146 |
0.00562778 |
0.00083109 |
0.00361433 |
0.98509 |
0.93606 |
max |
0.00343602 |
0.00733062 |
0.00100416 |
0.00431967 |
0.992209 |
0.961416 |
std |
0.000323328 |
0.000575117 |
5.78179e-05 |
0.000260594 |
0.00251692 |
0.0092393 |
MAE/ fold from 10-fold CV#
Alternative visual summary of input data for t-test
