Result Detail – Preprocessing Help

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Result Information
Result ID
34
Type
Preprocessing
Status
completed
Dataset ID
690
Created
2026-09-21 02:11:20.564609
Preprocessing Summary Help
Steps Applied
missing value imputation normalization
Rows (in → out)
400 → 400
Features
40
Target Column
PC_SHOOTMASS
Step Parameters
StepParameters
missing value imputation strategy = median
normalization method = z-score
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 #34)
Engine
Python · pandas/scikit-learn v3.0.3
Dataset(s)
#690 gallery — cat_g_field_data_plots.csv
Status
completed
Permanent link
https://cat-g-omxpert.wishartlab.com/results/by-token/eb7eb2770d9b4a1cbd47e9bc2da501e5 Bookmark or share this URL — it does not depend on your session.
Created
2026-09-21 02:11:20.564609

Parameters used

ParameterValue
normalization {'method': 'z-score'}
steps missing_value_imputation → normalization

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
df_out = service.apply(df, steps=steps, params=params)