Preprocessing Result #35 — Analysis Report

Generated 2026-10-14 12:52:27 · 1 run · CAT-G Data Analyzer

Download HTML report Download PDF report Download DOCX report Download Markdown Download MD + figures (zip)

Contents

1. preprocessing (#35) completed

1. Preprocessing 2026-09-21 02:12:55 · preprocessing

Preprocessing transformed the dataset from 393 rows to 393 rows with 33 output features.

n_rows_in	393
n_rows_out	393
n_features_out	33
target_col	PC_SHOOTMASS
derived_dataset_id	695

outlier report

name	value
method	iqr
handling	flag
n_outliers_detected	17
n_original	393
min_cols_required	4
n_removed	0
timing	before_split

before after boxplot

missingness heatmap

Method & Provenance

Method: Preprocessing
Engine: Python · pandas/scikit-learn 3.0.3
Input dataset: gallery — catg_example_01_forage_biomass.csv
Started: 2026-09-21 02:12:55.894015
Permanent link: https://cat-g-omxpert.wishartlab.com/results/by-token/3496fe33b6fd47cc9409f0c0d5edb0d3

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

Command history

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