Result Detail – Random Forest Help

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Result Information
Result ID
148
Type
Random Forest
Status
completed
Dataset ID
702
Created
2026-09-21 02:15:49.155216
Saved Model
Available — Download .pkl
Model Parameters
Model Type
regression
Estimators
60
Max Depth
None
Pre-Modeling Statistics (Pearson, Spearman, ANOVA) Help
Feature Pearson r Pearson p Pearson FDR Spearman ρ Spearman FDR ANOVA F ANOVA FDR Significant?
PLOT -0.8094 0.0000 0.0000 -0.7607 0.0000 178.5728 0.0000 ✓ Yes
ENV_SOILNH4 0.0826 0.4235 0.4941 0.2660 0.0123 0.6462 0.4941 ✓ Yes
ENV_SOILNO3 0.0429 0.6778 0.7492 -0.0032 0.9752 0.1737 0.7492 ✗ No
ENV_SOILP 0.1838 0.0730 0.0902 0.1593 0.1412 3.2876 0.0902 ✗ No
ENV_SOILOC 0.8337 0.0000 0.0000 0.8261 0.0000 214.2935 0.0000 ✓ Yes
ENV_SOILTN 0.8292 0.0000 0.0000 0.8689 0.0000 206.9389 0.0000 ✓ Yes
ENV_SOILTC 0.8201 0.0000 0.0000 0.8628 0.0000 193.0784 0.0000 ✓ Yes
ENV_PH -0.1949 0.0570 0.0798 -0.1089 0.3217 3.7128 0.0798 ✗ No
ENV_SOILCLAY 0.7880 0.0000 0.0000 0.7779 0.0000 153.9446 0.0000 ✓ Yes
ENV_SOILSILT 0.8273 0.0000 0.0000 0.8399 0.0000 203.9462 0.0000 ✓ Yes
ENV_SOILSAND -0.8430 0.0000 0.0000 -0.8509 0.0000 230.8978 0.0000 ✓ Yes
ENV_SOILMOIS 0.7658 0.0000 0.0000 0.7992 0.0000 133.3222 0.0000 ✓ Yes
PC_SHOOTMASS 0.4026 0.0000 0.0001 0.4904 0.0000 18.1837 0.0001 ✓ Yes
PC_ROOTMASS 0.0207 0.8414 0.8414 0.1807 0.0964 0.0403 0.8414 ✗ No
PC_LITTERMASS 0.1888 0.0655 0.0859 0.2578 0.0147 3.4742 0.0859 ✓ Yes
COVER_TOTAL_JUL 0.2255 0.0272 0.0408 0.3868 0.0001 5.0362 0.0408 ✓ Yes
COVER_SHANNON_JUL 0.0272 0.7927 0.8323 0.0335 0.7831 0.0695 0.8323 ✗ No
SOIL_EC_uS_cm -0.5998 0.0000 0.0000 -0.7424 0.0000 52.8183 0.0000 ✓ Yes
SOIL_CO2_mg_per_g 0.5712 0.0000 0.0000 0.7227 0.0000 45.5107 0.0000 ✓ Yes
BACTERIAL_NECROMASS_C 0.8041 0.0000 0.0000 0.8837 0.0000 172.0237 0.0000 ✓ Yes
FUNGAL_NECROMASS_C 0.9974 0.0000 0.0000 0.9885 0.0000 17705.0452 0.0000 ✓ Yes
Download CSV
Feature Importance (Random Forest) Help
Rank Feature Importance (Mean) SD
1 FUNGAL_NECROMASS_C 0.9260 0.0212
2 ENV_SOILSAND 0.0140 0.0118
3 ENV_SOILCLAY 0.0131 0.0070
4 ENV_SOILSILT 0.0068 0.0012
5 ENV_SOILTN 0.0063 0.0063
6 ENV_SOILMOIS 0.0060 0.0005
7 PLOT 0.0044 0.0014
8 ENV_SOILNH4 0.0043 0.0030
9 ENV_SOILTC 0.0038 0.0003
10 BACTERIAL_NECROMASS_C 0.0037 0.0021
11 ENV_SOILP 0.0024 0.0011
12 SOIL_CO2_mg_per_g 0.0016 0.0011
13 SOIL_EC_uS_cm 0.0015 0.0009
14 ENV_SOILOC 0.0013 0.0011
15 PC_SHOOTMASS 0.0012 0.0002
16 ENV_SOILNO3 0.0009 0.0005
17 COVER_SHANNON_JUL 0.0009 0.0008
18 COVER_TOTAL_JUL 0.0007 0.0003
19 ENV_PH 0.0004 0.0001
20 PC_LITTERMASS 0.0004 0.0000
21 PC_ROOTMASS 0.0001 0.0000
Download CSV
Permutation Importance Help
Rank Feature Perm. Importance (Mean) SD
1 FUNGAL_NECROMASS_C 1.4052 0.2257
2 ENV_SOILSAND 0.0032 0.0009
3 ENV_SOILTN 0.0023 0.0022
4 ENV_SOILCLAY 0.0020 0.0004
5 ENV_SOILMOIS 0.0020 0.0008
6 PLOT 0.0008 0.0013
7 ENV_SOILSILT 0.0007 0.0014
8 BACTERIAL_NECROMASS_C 0.0006 0.0011
9 ENV_SOILTC 0.0004 0.0002
10 SOIL_EC_uS_cm 0.0002 0.0004
11 COVER_TOTAL_JUL 0.0002 0.0002
12 COVER_SHANNON_JUL 0.0001 0.0002
13 ENV_SOILNO3 0.0001 0.0004
14 SOIL_CO2_mg_per_g 0.0001 0.0001
15 PC_SHOOTMASS 0.0001 0.0005
16 ENV_SOILOC 0.0000 0.0003
17 PC_ROOTMASS 0.0000 0.0000
18 ENV_PH -0.0001 0.0002
19 PC_LITTERMASS -0.0002 0.0000
20 ENV_SOILP -0.0005 0.0008
21 ENV_SOILNH4 -0.0031 0.0041
Download CSV
SHAP Feature Importance Help
Rank Feature SHAP Mean |Abs|
1 FUNGAL_NECROMASS_C 16.6986
2 ENV_SOILSAND 0.7500
3 ENV_SOILCLAY 0.5589
4 ENV_SOILSILT 0.4159
5 ENV_SOILMOIS 0.3264
6 BACTERIAL_NECROMASS_C 0.2012
7 PLOT 0.1960
8 ENV_SOILTC 0.1860
9 ENV_SOILNH4 0.1098
10 ENV_SOILP 0.1009
11 ENV_SOILTN 0.0777
12 ENV_SOILNO3 0.0642
13 SOIL_EC_uS_cm 0.0606
14 PC_SHOOTMASS 0.0454
15 COVER_SHANNON_JUL 0.0260
16 PC_LITTERMASS 0.0259
17 COVER_TOTAL_JUL 0.0243
18 ENV_PH 0.0223
19 ENV_SOILOC 0.0173
20 SOIL_CO2_mg_per_g 0.0111
21 PC_ROOTMASS 0.0086
Download CSV
Model Metrics
Split R² MSE
Split 1 0.9906 3.0794
Split 2 0.8600 73.6160
Split 3 0.9562 22.0457
Mean 0.9356 32.9137
Download CSV
Figures
Feature importance Download PNG
Feature importance
Permutation importance Download PNG
Permutation importance
SHAP summary Download PNG
SHAP summary
Observed vs predicted (out-of-fold) Download PNG
Observed vs predicted (out-of-fold)
Cross-validation score distribution Download PNG
Cross-validation score distribution
Pathway Analysis (same dataset) Help
Run Pathway Analysis

Method & Provenance

Method
Random Forest (Regression)
Method key
random_forest (result type: random_forest, result #148)
Engine
Python · scikit-learn v1.8.0
Dataset(s)
#702 gallery — catg_example_07_microbial_soil_biology.csv
Status
completed
Permanent link
https://cat-g-omxpert.wishartlab.com/results/by-token/8705c62fa577496199d0d6e6fc4f47a1 Bookmark or share this URL — it does not depend on your session.
Created
2026-09-21 02:15:49.155216

Parameters used

ParameterValue
task_type regression
model_type regression
target_column MICROBIAL_NECROMASS_C
n_estimators 60
n_splits 3
test_size 0.25
run_univariate True
run_permutation True
run_shap True
permutation_repeats 10
fdr_threshold 0.05

Execution trace

Reconstructed from the parameters stored with this result — represents the Python/R calls the analysis service made. 

from sklearn.ensemble import RandomForestRegressor
model = RandomForestRegressor(n_estimators=60, random_state=42)
scores = sklearn.model_selection.cross_val_score(model, X, y, cv=3)