# Ml Result Result #100 — Analysis Report

Generated 2026-09-21 02:36:02 · 1 run(s) · CAT-G Data Analyzer

## 1. model comparison (#100)

2026-09-21 02:12:18 · ml_result · status: completed

*Random Forest scored highest under cross-validation (r2 = 0.537).*

### model metrics

| Model | Metric | r2 mean | mse mean |
|---|---|---|---|
| Linear Regression | r2 | 0.399377 | 52.450519 |
| Random Forest | r2 | 0.536964 | 40.236422 |
| K-Nearest Neighbours | r2 | 0.374541 | 53.689833 |

![metric 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)

*metric bars*

![cv boxplot](data:image/png;base64,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)

*cv boxplot*

### Method & Provenance

- **Method:** Model Comparison
- **Engine:** Python · scikit-learn 1.8.0
- **Input datasets:** gallery — cat_g_field_data_plots.csv
- **Started:** 2026-09-21 02:12:18.862020
- **Permanent link:** https://cat-g-omxpert.wishartlab.com/results/by-token/c53fa74c83ff4edc88d28c8b5ac82e48

| Parameter | Value |
|---|---|
| task_type | regression |
| model_type | model_comparison |
| target_column | PC_SHOOTMASS |
| n_splits | 3 |

**Command history**

```python
# task_type = 'regression'
```

```python
# Models compared via app.services.ml_model_registry
```

```python
scores = sklearn.model_selection.cross_val_score(model, X, y, cv=3)
```