Dataset

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Model Settings

OLS

Ordinary Least Squares parameters

Fit Intercept

Include bias term in the model

Positive Coefficients

Constrain all weights ≥ 0 (NNLS)

Regularization (α)0.0

0 = OLS10.0 = strong

Train / Test Split

Holdout proportion for evaluation

Test Size20%

Train: 80%Test: 20%

Preprocessing

Feature transformations

Enable preprocessing

Advanced settings

Projection

2D visualization method

PCA for quick linear projection. UMAP for complex manifolds.

Parameter Guide

Click to expand

Performance Metrics

R²

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Awaiting training

RMSE

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Awaiting training

MAE

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Awaiting training

Adj. R²

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Awaiting training

Train R²

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Awaiting training

Samples

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Awaiting training

Actual vs Predicted

Train the model to see actual vs predicted scatter

Advanced Analysis

Deep Dive Analysis

Run training to populate analysis

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Job History

Recent jobs — auto-pruned to keep 10 per type

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Linear Regression — Interactive Analysis