Result Detail – Ml Result

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Result Information

Result ID: 100
Type: Ml Result
Status: completed
Dataset ID: 690
Created: 2026-09-21 02:12:18.862020

ML Pipeline — Model Comparison Regression

Model: Model Comparison
Target Column: PC_SHOOTMASS
CV Splits: 3
model_keys: ['linear_regression', 'random_forest', 'knn']
task_type: regression
scoring: r2

Model	R² Mean	R² Std	MSE Mean	MSE Std
Linear Regression	0.3994	0.0317	52.4505	7.1964
Random Forest	0.5370	0.0176	40.2364	3.6792
K-Nearest Neighbours	0.3745	0.0876	53.6898	1.7886

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Feature importance not available for this model.

Permutation importance was not included in this run.

SHAP analysis was not included in this run.

Feature	Pearson r	Pearson p	Pearson FDR	Spearman ρ	Spearman FDR	ANOVA F	ANOVA FDR	Significant?
PLOT	0.8952	0.0000	0.0000	0.8153	0.0000	1605.8002	0.0000	✓ Yes
LAT	-0.9550	0.0000	0.0000	-0.8525	0.0000	4126.3969	0.0000	✓ Yes
LONG	-0.9545	0.0000	0.0000	-0.8525	0.0000	4078.3374	0.0000	✓ Yes
ENV_SOILNH4	-0.0573	0.2525	0.3697	-0.1994	0.0001	1.3133	0.3697	✓ Yes
ENV_SOILNO3	-0.0521	0.2982	0.4216	-0.1840	0.0004	1.0851	0.4216	✓ Yes
ENV_SOILP	-0.1568	0.0017	0.0028	-0.1626	0.0018	10.0274	0.0028	✓ Yes
ENV_SOILOC	-0.8084	0.0000	0.0000	-0.8350	0.0000	750.4927	0.0000	✓ Yes
ENV_SOILTN	-0.7951	0.0000	0.0000	-0.8392	0.0000	684.0067	0.0000	✓ Yes
ENV_SOILTC	-0.7958	0.0000	0.0000	-0.8413	0.0000	687.3832	0.0000	✓ Yes
ENV_PH	0.0626	0.2114	0.3211	0.0222	0.7487	1.5667	0.3211	✗ No
ENV_SOILCLAY	-0.8632	0.0000	0.0000	-0.8521	0.0000	1163.0139	0.0000	✓ Yes
ENV_SOILSILT	-0.8724	0.0000	0.0000	-0.8452	0.0000	1268.1428	0.0000	✓ Yes
ENV_SOILSAND	0.9059	0.0000	0.0000	0.8520	0.0000	1820.1391	0.0000	✓ Yes
ENV_SOILMOIS	-0.7940	0.0000	0.0000	-0.8296	0.0000	679.0502	0.0000	✓ Yes
RC_SHOOTMASS	-0.4235	0.0000	0.0000	-0.4822	0.0000	87.0006	0.0000	✓ Yes
RC_WOODMASS	-0.1440	0.0039	0.0064	-0.1116	0.0388	8.4303	0.0064	✓ Yes
RC_LITTERMASS	-0.0831	0.0968	0.1527	-0.0534	0.3831	2.7702	0.1527	✗ No
RC_LITTERWMASS	0.0344	0.4927	0.6320	-0.0138	0.8454	0.4716	0.6320	✗ No
PC_SHOOTMASS	-0.3745	0.0000	0.0000	-0.3795	0.0000	64.9322	0.0000	✓ Yes
PC_WOODMASS	-0.2071	0.0000	0.0001	-0.1611	0.0019	17.8376	0.0001	✓ Yes
PC_LITTERMASS	-0.0270	0.5909	0.6730	-0.0175	0.8057	0.2894	0.6730	✗ No
PC_LITTERWMASS	0.0307	0.5409	0.6609	-0.0555	0.3788	0.3745	0.6609	✗ No
PC_ROOTMASS	0.0000	1.0000	1.0000	-0.2915	0.0000	0.0000	1.0000	✓ Yes
PC_HEIGHT	-0.3426	0.0000	0.0000	-0.3328	0.0000	52.9154	0.0000	✓ Yes
GH_COUNT	0.5494	0.0000	0.0000	0.5589	0.0000	172.0343	0.0000	✓ Yes
ENV_AIRTEMP	-0.0047	0.9246	1.0000	0.0102	0.8818	0.0090	1.0000	✗ No
COVER_RICHNESS_JUN	0.0024	0.9614	1.0000	0.0068	0.9142	0.0024	1.0000	✗ No
COVER_TOTAL_JUN	-0.3898	0.0000	0.0000	-0.5642	0.0000	71.3029	0.0000	✓ Yes
COVER_SHANNON_JUN	0.0013	0.9794	1.0000	-0.0003	0.9959	0.0007	1.0000	✗ No
COVER_RICHNESS_JUL	0.0344	0.4932	0.6320	0.0424	0.5098	0.4703	0.6320	✗ No
COVER_TOTAL_JUL	-0.2408	0.0000	0.0000	-0.3596	0.0000	24.4993	0.0000	✓ Yes
COVER_SHANNON_JUL	0.0289	0.5642	0.6609	0.0308	0.6697	0.3331	0.6609	✗ No
COVER_RICHNESS_AUG	-0.0297	0.5540	0.6609	-0.0250	0.7359	0.3508	0.6609	✗ No
COVER_TOTAL_AUG	-0.3131	0.0000	0.0000	-0.3692	0.0000	43.2471	0.0000	✓ Yes
COVER_SHANNON_AUG	-0.0354	0.4797	0.6320	-0.0531	0.3831	0.5004	0.6320	✗ No
PASTURE_TOTALAREA	0.9196	0.0000	0.0000	0.8555	0.0000	2180.9712	0.0000	✓ Yes
SUBPASTURE_TOTALAREA	0.8608	0.0000	0.0000	0.8378	0.0000	1138.4023	0.0000	✓ Yes
PASTURE_FORESTAREA	-0.7406	0.0000	0.0000	-0.7560	0.0000	483.6219	0.0000	✓ Yes
PASTURE_WETLANDAREA	0.2248	0.0000	0.0000	0.0838	0.1381	21.1870	0.0000	✓ Yes
SUBPASTURE_FORESTAREA	-0.3814	0.0000	0.0000	-0.3340	0.0000	67.7412	0.0000	✓ Yes
SUBPASTURE_WETLANDAREA	0.0005	0.9928	1.0000	0.0243	0.7359	0.0001	1.0000	✗ No

Figures

Model comparison Download PNG

Cross-validation score distribution Download PNG

Pathway Analysis (same dataset)

Run Pathway Analysis

Method & Provenance

Method: Model Comparison
Method key: ml_result (result type: ml_result, result #100)
Engine: Python · scikit-learn v1.8.0
Dataset(s): #690 gallery — cat_g_field_data_plots.csv
Status: completed
Permanent link: https://cat-g-omxpert.wishartlab.com/results/by-token/c53fa74c83ff4edc88d28c8b5ac82e48 Bookmark or share this URL — it does not depend on your session.
Created: 2026-09-21 02:12:18.862020

Parameters used

Parameter	Value
`task_type`	regression
`model_type`	model_comparison
`target_column`	PC_SHOOTMASS
`n_splits`	3

Execution trace

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

# task_type = 'regression'

# Models compared via app.services.ml_model_registry

scores = sklearn.model_selection.cross_val_score(model, X, y, cv=3)