Ml Result Result #102 — Analysis Report

Generated 2026-09-21 02:38:00 · 1 run · CAT-G Data Analyzer

Contents

model comparison (#102) completed

1. Model Comparison 2026-09-21 02:16:32 · ml_result

Logistic Regression scored highest under cross-validation (f1_weighted = 0.951).

model metrics

Model	Metric	score mean	score std	accuracy mean	f1 mean
Logistic Regression	f1_weighted	0.95055	0.053141	0.95	0.95055
Random Forest	f1_weighted	0.95021	0.034943	0.95	0.95021
K-Nearest Neighbours	f1_weighted	0.95055	0.053141	0.95	0.95055

metric bars

cv boxplot

Method & Provenance

Method: Model Comparison
Engine: Python · scikit-learn 1.8.0
Input dataset: gallery — example_classification.csv
Started: 2026-09-21 02:16:32.038299
Permanent link: https://cat-g-omxpert.wishartlab.com/results/by-token/a5a1439572d3484fab634cd6bbefcccd

Parameter	Value
task_type	classification
model_type	model_comparison
target_column	target
n_splits	3

Command history

# python
# task_type = 'classification'
# python
# Models compared via app.services.ml_model_registry
# python
scores = sklearn.model_selection.cross_val_score(model, X, y, cv=3)