Result Detail – Preprocessing Help

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Result Information
Result ID
35
Type
Preprocessing
Status
completed
Dataset ID
694
Created
2026-09-21 02:12:55.894015
Preprocessing Summary Help
Steps Applied
missing value imputation normalization outlier handling
Rows (in → out)
393 → 393
Features
33
Target Column
PC_SHOOTMASS

Outliers detected: 17 (0 removed, method: iqr, handling: flag, min outlying columns: 4)

Step Parameters
StepParameters
missing value imputation strategy = knn
normalization method = min-max
outlier handling method = iqr handling = flag min_col_fraction = 0.1
Figures
Before vs after Download PNG
Before vs after
Missing values Download PNG
Missing values
Pathway Analysis (same dataset) Help
Run Pathway Analysis

Method & Provenance

Method
Preprocessing
Method key
preprocessing (result type: preprocessing, result #35)
Engine
Python · pandas/scikit-learn v3.0.3
Dataset(s)
#694 gallery — catg_example_01_forage_biomass.csv
Status
completed
Permanent link
https://cat-g-omxpert.wishartlab.com/results/by-token/3496fe33b6fd47cc9409f0c0d5edb0d3 Bookmark or share this URL — it does not depend on your session.
Created
2026-09-21 02:12:55.894015

Parameters used

ParameterValue
normalization {'method': 'min-max'}
outlier_handling {'method': 'iqr', 'handling': 'flag', 'min_col_fraction': 0.1}
steps missing_value_imputation → normalization → outlier_handling

Execution trace

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

# app.services.preprocessing_service.PreprocessingService
# step: missing_value_imputation
# step: normalization
# step: outlier_handling
df_out = service.apply(df, steps=steps, params=params)