Result Detail – Random Forest Help

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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) Help

Feature	Pearson r	Pearson p	Pearson FDR	Spearman ρ	Spearman FDR	ANOVA F	ANOVA FDR	Significant?
PLOT	-0.3566	0.0000	0.0000	-0.2676	0.0000	57.9998	0.0000	✓ Yes
LAT	0.3911	0.0000	0.0000	0.2634	0.0000	71.8502	0.0000	✓ Yes
LONG	0.3848	0.0000	0.0000	0.2388	0.0000	69.1789	0.0000	✓ Yes
ENV_SOILNH4	0.0824	0.0996	0.1208	0.1870	0.0002	2.7239	0.1208	✓ Yes
ENV_SOILNO3	0.0367	0.4639	0.5015	0.0933	0.0691	0.5376	0.5015	✗ No
ENV_SOILP	0.2028	0.0000	0.0001	0.1271	0.0133	17.0726	0.0001	✓ Yes
ENV_SOILOC	0.4830	0.0000	0.0000	0.4605	0.0000	121.1279	0.0000	✓ Yes
ENV_SOILTN	0.4801	0.0000	0.0000	0.4567	0.0000	119.2385	0.0000	✓ Yes
ENV_SOILTC	0.4829	0.0000	0.0000	0.4597	0.0000	121.0029	0.0000	✓ Yes
ENV_PH	-0.0157	0.7540	0.7540	-0.0332	0.5344	0.0983	0.7540	✗ No
ENV_SOILCLAY	0.3541	0.0000	0.0000	0.3538	0.0000	57.0470	0.0000	✓ Yes
ENV_SOILSILT	0.4306	0.0000	0.0000	0.4009	0.0000	90.5771	0.0000	✓ Yes
ENV_SOILSAND	-0.4124	0.0000	0.0000	-0.3838	0.0000	81.5668	0.0000	✓ Yes
ENV_SOILMOIS	0.4614	0.0000	0.0000	0.4451	0.0000	107.6683	0.0000	✓ Yes
RC_SHOOTMASS	0.5332	0.0000	0.0000	0.6073	0.0000	158.0640	0.0000	✓ Yes
RC_WOODMASS	0.1152	0.0212	0.0283	0.1585	0.0019	5.3525	0.0283	✓ Yes
RC_LITTERMASS	0.4564	0.0000	0.0000	0.3922	0.0000	104.7397	0.0000	✓ Yes
RC_LITTERWMASS	0.0591	0.2383	0.2724	0.1293	0.0120	1.3947	0.2724	✓ Yes
PC_WOODMASS	0.2348	0.0000	0.0000	0.2313	0.0000	23.2218	0.0000	✓ Yes
PC_LITTERMASS	0.4327	0.0000	0.0000	0.4261	0.0000	91.6693	0.0000	✓ Yes
PC_LITTERWMASS	0.1439	0.0039	0.0058	0.1252	0.0144	8.4115	0.0058	✓ Yes
PC_ROOTMASS	0.1007	0.0442	0.0571	0.2809	0.0000	4.0741	0.0571	✓ Yes
PC_HEIGHT	0.4465	0.0000	0.0000	0.4329	0.0000	99.0837	0.0000	✓ Yes
GH_COUNT	-0.2974	0.0000	0.0000	-0.2940	0.0000	38.6160	0.0000	✓ Yes
ENV_AIRTEMP	0.0247	0.6220	0.6379	-0.0142	0.7971	0.2435	0.6379	✗ No
COVER_RICHNESS_JUN	-0.1236	0.0134	0.0185	-0.2189	0.0000	6.1702	0.0185	✓ Yes
COVER_TOTAL_JUN	0.3239	0.0000	0.0000	0.3605	0.0000	46.6550	0.0000	✓ Yes
COVER_SHANNON_JUN	-0.1286	0.0100	0.0143	-0.2196	0.0000	6.6913	0.0143	✓ Yes
COVER_RICHNESS_JUL	-0.0938	0.0609	0.0761	-0.1713	0.0008	3.5336	0.0761	✓ Yes
COVER_TOTAL_JUL	0.3024	0.0000	0.0000	0.4263	0.0000	40.0461	0.0000	✓ Yes
COVER_SHANNON_JUL	-0.0286	0.5682	0.5981	-0.1044	0.0421	0.3263	0.5981	✓ Yes
COVER_RICHNESS_AUG	-0.1785	0.0003	0.0005	-0.2616	0.0000	13.0987	0.0005	✓ Yes
COVER_TOTAL_AUG	0.3798	0.0000	0.0000	0.4245	0.0000	67.0752	0.0000	✓ Yes
COVER_SHANNON_AUG	-0.1615	0.0012	0.0018	-0.2277	0.0000	10.6585	0.0018	✓ Yes
PASTURE_TOTALAREA	-0.3966	0.0000	0.0000	-0.3771	0.0000	74.3077	0.0000	✓ Yes
SUBPASTURE_TOTALAREA	-0.3128	0.0000	0.0000	-0.3020	0.0000	43.1698	0.0000	✓ Yes
PASTURE_FORESTAREA	0.2953	0.0000	0.0000	0.2456	0.0000	38.0232	0.0000	✓ Yes
PASTURE_WETLANDAREA	-0.0716	0.1531	0.1802	0.0093	0.8533	2.0486	0.1802	✗ No
SUBPASTURE_FORESTAREA	0.2507	0.0000	0.0000	0.2206	0.0000	26.6878	0.0000	✓ Yes
SUBPASTURE_WETLANDAREA	0.0440	0.3797	0.4219	0.0704	0.1730	0.7734	0.4219	✗ No

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Feature Importance (Random Forest) Help

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 Help

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 Help

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 Help

		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) Help

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)