Result Detail – Clustering Help

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Result Information
Result ID
32
Type
Clustering
Status
completed
Dataset ID
690
Created
2026-09-21 02:12:45.307195
Clustering Result – Kmeans Help
Method
Kmeans
Clusters (k)
3
Silhouette score
0.1525 (higher = better separated)
Rows clustered
59 (341 rows dropped for missing values)
Feature columns
PLOT, LAT, LONG, ENV_SOILNH4, ENV_SOILNO3, ENV_SOILP, ENV_SOILOC, ENV_SOILTN, ENV_SOILTC, ENV_PH, ENV_SOILCLAY, ENV_SOILSILT, ENV_SOILSAND, ENV_SOILMOIS, RC_SHOOTMASS, RC_WOODMASS, RC_LITTERMASS, RC_LITTERWMASS, PC_SHOOTMASS, PC_WOODMASS, PC_LITTERMASS, PC_LITTERWMASS, PC_ROOTMASS, PC_HEIGHT, GH_COUNT, ENV_AIRTEMP, COVER_RICHNESS_JUN, COVER_TOTAL_JUN, COVER_SHANNON_JUN, COVER_RICHNESS_JUL, COVER_TOTAL_JUL, COVER_SHANNON_JUL, COVER_RICHNESS_AUG, COVER_TOTAL_AUG, COVER_SHANNON_AUG, PASTURE_TOTALAREA, SUBPASTURE_TOTALAREA, PASTURE_FORESTAREA, PASTURE_WETLANDAREA, SUBPASTURE_FORESTAREA, SUBPASTURE_WETLANDAREA
Cluster sizes Help
Cluster 0: n=9 Cluster 1: n=35 Cluster 2: n=15
Per-cluster feature means Help
Cluster PLOT LAT LONG ENV_SOILNH4 ENV_SOILNO3 ENV_SOILP ENV_SOILOC ENV_SOILTN ENV_SOILTC ENV_PH ENV_SOILCLAY ENV_SOILSILT ENV_SOILSAND ENV_SOILMOIS RC_SHOOTMASS RC_WOODMASS RC_LITTERMASS RC_LITTERWMASS PC_SHOOTMASS PC_WOODMASS PC_LITTERMASS PC_LITTERWMASS PC_ROOTMASS PC_HEIGHT GH_COUNT ENV_AIRTEMP COVER_RICHNESS_JUN COVER_TOTAL_JUN COVER_SHANNON_JUN COVER_RICHNESS_JUL COVER_TOTAL_JUL COVER_SHANNON_JUL COVER_RICHNESS_AUG COVER_TOTAL_AUG COVER_SHANNON_AUG PASTURE_TOTALAREA SUBPASTURE_TOTALAREA PASTURE_FORESTAREA PASTURE_WETLANDAREA SUBPASTURE_FORESTAREA SUBPASTURE_WETLANDAREA
0 580.4 50.88 -111.9 5.363 1.465 0.3329 0.8041 0.1063 1.192 7.386 3.343 7.39 89.26 3.105 16.89 0.1416 22.38 0 11.01 0.1181 22.29 0.3388 7.05 54.57 33.71 24.29 24.78 279.2 2.365 24.56 285.5 2.209 11.67 140.6 1.494 128.2 10.37 4.589 8.294 0.2519 0.7285
1 579.1 50.88 -111.9 7.764 4.553 0.1553 0.7542 0.101 1.11 7.185 3.249 5.988 90.76 2.64 13.22 0.2014 19.01 0.3088 10.12 0.1836 22.49 0.2948 4.929 54.82 48.4 22.07 12.03 122.4 1.644 12.43 147.6 1.572 12.23 135.6 1.483 128.3 10.64 4.642 7.333 0.4134 0.645
2 661.9 50.86 -111.9 15.15 12.97 0.3013 1.079 0.118 1.306 7.322 4.458 9.207 86.33 4.83 18.61 0.2566 30.27 0 15.63 0.245 23.93 0.3716 5.324 61.24 65.6 21.08 9.8 138.4 1.331 9.4 149.5 1.239 8.133 137.7 1.114 120.3 10.06 2.854 5.728 0.361 0.7053
Figures
Cluster scatter Download PNG
Cluster scatter
Silhouette plot Download PNG
Silhouette plot
Elbow plot Download PNG
Elbow plot
Pathway Analysis (same dataset) Help
Run Pathway Analysis

Method & Provenance

Method
Clustering — K-Means
Method key
kmeans (result type: clustering, result #32)
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/a038a07d3c7e4e02ab3ee272769ecd2c Bookmark or share this URL — it does not depend on your session.
Created
2026-09-21 02:12:45.307195

Parameters used

ParameterValue
cluster_method kmeans
feature_cols PLOT, LAT, LONG, ENV_SOILNH4, ENV_SOILNO3, ENV_SOILP, ENV_SOILOC, ENV_SOILTN, ENV_SOILTC, ENV_PH, ENV_SOILCLAY, ENV_SOILSILT, ENV_SOILSAND, ENV_SOILMOIS, RC_SHOOTMASS, RC_WOODMASS, RC_LITTERMASS, RC_LITTERWMASS, PC_SHOOTMASS, PC_WOODMASS, PC_LITTERMASS, PC_LITTERWMASS, PC_ROOTMASS, PC_HEIGHT, GH_COUNT, ENV_AIRTEMP, COVER_RICHNESS_JUN, COVER_TOTAL_JUN, COVER_SHANNON_JUN, COVER_RICHNESS_JUL, COVER_TOTAL_JUL, COVER_SHANNON_JUL, COVER_RICHNESS_AUG, COVER_TOTAL_AUG, COVER_SHANNON_AUG, PASTURE_TOTALAREA, SUBPASTURE_TOTALAREA, PASTURE_FORESTAREA, PASTURE_WETLANDAREA, SUBPASTURE_FORESTAREA, SUBPASTURE_WETLANDAREA
n_clusters 3

Execution trace

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

from sklearn.cluster import KMeans
labels = KMeans(n_clusters=3, n_init=10, random_state=42).fit_predict(X)
silhouette = sklearn.metrics.silhouette_score(X, labels)