Result Detail – Random Forest

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Result Information

Result ID: 140
Type: Random Forest
Status: completed
Dataset ID: 690
Created: 2026-09-21 02:12:05.989988
Saved Model: Available — Download .pkl

Possible data leakage detected:

Feature "LAT" is almost perfectly correlated with the target "RANCH" (r = -0.955) — likely data leakage or a duplicate measurement; consider excluding it.
Feature "LONG" is almost perfectly correlated with the target "RANCH" (r = -0.955) — likely data leakage or a duplicate measurement; consider excluding it.
Feature "ENV_SOILSAND" is almost perfectly correlated with the target "RANCH" (r = 0.906) — likely data leakage or a duplicate measurement; consider excluding it.
Feature "PASTURE_TOTALAREA" is almost perfectly correlated with the target "RANCH" (r = 0.920) — likely data leakage or a duplicate measurement; consider excluding it.
Identifier-like column(s) used as features: PLOT. These are bookkeeping fields; high importance for them usually reflects row ordering, not biology. Consider excluding them.
Spatial confounding risk: coordinate column(s) LAT, LONG rank among the most important features. The model may be learning field position rather than biological signal; interpret with care or exclude coordinates.

Model Parameters

Model Type: classification
Estimators: 60
Max Depth: None

Pre-Modeling Statistics (Pearson, Spearman, ANOVA)

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

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Feature Importance (Random Forest)

Rank	Feature	Importance (Mean)	SD
1	LONG	0.2022	0.0217
2	PLOT	0.1676	0.0148
3	PASTURE_TOTALAREA	0.1031	0.0211
4	ENV_SOILCLAY	0.0897	0.0344
5	ENV_SOILSAND	0.0738	0.0084
6	ENV_SOILOC	0.0607	0.0078
7	LAT	0.0607	0.0013
8	SUBPASTURE_TOTALAREA	0.0525	0.0136
9	ENV_SOILTN	0.0522	0.0073
10	PASTURE_FORESTAREA	0.0362	0.0003
11	ENV_SOILTC	0.0333	0.0045
12	ENV_SOILSILT	0.0171	0.0003
13	PC_ROOTMASS	0.0156	0.0006
14	ENV_SOILMOIS	0.0147	0.0004
15	COVER_TOTAL_JUN	0.0066	0.0003
16	GH_COUNT	0.0059	0.0004
17	PASTURE_WETLANDAREA	0.0048	0.0010
18	SUBPASTURE_FORESTAREA	0.0008	0.0007
19	COVER_RICHNESS_AUG	0.0005	0.0002
20	COVER_TOTAL_AUG	0.0005	0.0004
21	PC_WOODMASS	0.0003	0.0002
22	COVER_RICHNESS_JUL	0.0002	0.0003
23	COVER_SHANNON_JUN	0.0002	0.0002
24	COVER_SHANNON_AUG	0.0002	0.0002
25	SUBPASTURE_WETLANDAREA	0.0001	0.0001
26	COVER_RICHNESS_JUN	0.0001	0.0001
27	COVER_TOTAL_JUL	0.0001	0.0001
28	RC_LITTERWMASS	0.0001	0.0001
29	PC_SHOOTMASS	0.0001	0.0001
30	PC_LITTERWMASS	0.0001	0.0001
31	RC_LITTERMASS	0.0001	0.0001
32	ENV_AIRTEMP	0.0000	0.0001
33	RC_WOODMASS	0.0000	0.0000
34	ENV_SOILNO3	0.0000	0.0000
35	ENV_PH	0.0000	0.0000
36	ENV_SOILP	0.0000	0.0000
37	PC_HEIGHT	0.0000	0.0000
38	RC_SHOOTMASS	0.0000	0.0000
39	COVER_SHANNON_JUL	0.0000	0.0000
40	ENV_SOILNH4	0.0000	0.0000
41	PC_LITTERMASS	0.0000	0.0000

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Permutation Importance

Rank	Feature	Perm. Importance (Mean)	SD
1	LONG	0.0110	0.0050
2	ENV_SOILCLAY	0.0093	0.0066
3	PASTURE_TOTALAREA	0.0093	0.0132
4	SUBPASTURE_TOTALAREA	0.0093	0.0132
5	COVER_RICHNESS_AUG	0.0070	0.0099
6	ENV_SOILSAND	0.0050	0.0071
7	COVER_TOTAL_AUG	0.0050	0.0071
8	LAT	0.0047	0.0066
9	ENV_SOILOC	0.0047	0.0066
10	PC_ROOTMASS	0.0037	0.0052
11	PLOT	0.0000	0.0000
12	ENV_SOILNH4	0.0000	0.0000
13	ENV_SOILNO3	0.0000	0.0000
14	ENV_SOILP	0.0000	0.0000
15	ENV_SOILTN	0.0000	0.0000
16	ENV_SOILTC	0.0000	0.0000
17	ENV_PH	0.0000	0.0000
18	ENV_SOILSILT	0.0000	0.0000
19	ENV_SOILMOIS	0.0000	0.0000
20	RC_SHOOTMASS	0.0000	0.0000
21	RC_WOODMASS	0.0000	0.0000
22	RC_LITTERMASS	0.0000	0.0000
23	RC_LITTERWMASS	0.0000	0.0000
24	PC_SHOOTMASS	0.0000	0.0000
25	PC_WOODMASS	0.0000	0.0000
26	PC_LITTERMASS	0.0000	0.0000
27	PC_LITTERWMASS	0.0000	0.0000
28	PC_HEIGHT	0.0000	0.0000
29	GH_COUNT	0.0000	0.0000
30	ENV_AIRTEMP	0.0000	0.0000
31	COVER_RICHNESS_JUN	0.0000	0.0000
32	COVER_TOTAL_JUN	0.0000	0.0000
33	COVER_SHANNON_JUN	0.0000	0.0000
34	COVER_RICHNESS_JUL	0.0000	0.0000
35	COVER_TOTAL_JUL	0.0000	0.0000
36	COVER_SHANNON_JUL	0.0000	0.0000
37	COVER_SHANNON_AUG	0.0000	0.0000
38	PASTURE_FORESTAREA	0.0000	0.0000
39	PASTURE_WETLANDAREA	0.0000	0.0000
40	SUBPASTURE_FORESTAREA	0.0000	0.0000
41	SUBPASTURE_WETLANDAREA	0.0000	0.0000

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SHAP Feature Importance

Rank	Feature	SHAP Mean \|Abs\|
1	LONG	0.0779
2	PLOT	0.0662
3	PASTURE_TOTALAREA	0.0505
4	ENV_SOILCLAY	0.0339
5	LAT	0.0263
6	SUBPASTURE_TOTALAREA	0.0197
7	ENV_SOILSAND	0.0195
8	ENV_SOILTN	0.0139
9	ENV_SOILOC	0.0134
10	ENV_SOILTC	0.0131
11	PASTURE_FORESTAREA	0.0130
12	PC_ROOTMASS	0.0054
13	ENV_SOILSILT	0.0052
14	ENV_SOILMOIS	0.0037
15	COVER_TOTAL_JUN	0.0021
16	PASTURE_WETLANDAREA	0.0018
17	GH_COUNT	0.0018
18	PC_SHOOTMASS	0.0007
19	COVER_TOTAL_AUG	0.0006
20	COVER_SHANNON_AUG	0.0006
21	COVER_RICHNESS_AUG	0.0005
22	COVER_RICHNESS_JUN	0.0004
23	SUBPASTURE_FORESTAREA	0.0003
24	ENV_SOILNO3	0.0003
25	SUBPASTURE_WETLANDAREA	0.0003
26	PC_LITTERWMASS	0.0003
27	PC_WOODMASS	0.0003
28	COVER_SHANNON_JUN	0.0003
29	RC_LITTERWMASS	0.0002
30	ENV_SOILNH4	0.0000
31	ENV_SOILP	0.0000
32	ENV_PH	0.0000
33	RC_SHOOTMASS	0.0000
34	RC_WOODMASS	0.0000
35	RC_LITTERMASS	0.0000
36	PC_LITTERMASS	0.0000
37	PC_HEIGHT	0.0000
38	ENV_AIRTEMP	0.0000
39	COVER_RICHNESS_JUL	0.0000
40	COVER_TOTAL_JUL	0.0000
41	COVER_SHANNON_JUL	0.0000

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Model Metrics

Classification

Split	Accuracy	F1 (weighted)
Split 1	1.0000	1.0000
Split 2	1.0000	1.0000
Split 3	1.0000	1.0000
Mean	1.0000	1.0000

Confusion Matrix

		KINSELLA	MATTHEIS
	6	0	0
KINSELLA	0	138	0
MATTHEIS	0	0	156

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Figures

Feature importance Download PNG

Permutation importance Download PNG

SHAP summary Download PNG

Confusion matrix Download PNG

Cross-validation score distribution Download PNG

Pathway Analysis (same dataset)

Run Pathway Analysis

Method & Provenance

Method: Random Forest (Classification)
Method key: random_forest (result type: random_forest, result #140)
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/76d644e54c38460abc9ca6f21474ff98 Bookmark or share this URL — it does not depend on your session.
Created: 2026-09-21 02:12:05.989988

Parameters used

Parameter	Value
`task_type`	classification
`model_type`	classification
`target_column`	RANCH
`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 RandomForestClassifier

model = RandomForestClassifier(n_estimators=60, random_state=42)

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