YAML Metadata
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empty or missing yaml metadata in repo card
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---
library_name: sklearn
tags:
- sklearn
- regression
- embeddings
- weight-prediction
- ridge
model-index:
- name: Ridge Regression
results:
- task:
type: regression
name: Embedding Weight Prediction
metrics:
- type: mse
value: 0.752126161053798
name: Test MSE
- type: r2
value: -0.03790253867179685
name: Test R²
---
# Ridge Regression Weight Predictor
Linear model with L2 regularization for handling multicollinearity
## Performance Metrics
- Training Time: 15.79 seconds
- Training MSE: 0.460125
- Testing MSE: 0.752126
- Training R²: 0.384710
- Testing R²: -0.037903
## Model Analysis
### Predictions vs True Values

This plot shows how well the model's predictions match the true values:
- Points on the red line indicate perfect predictions
- Spread around the line shows prediction uncertainty
- Systematic deviations indicate bias
### Error Distribution

This plot shows the distribution of prediction errors:
- Centered around zero indicates unbiased predictions
- Width shows prediction precision
- Shape reveals error patterns
### Dimension-wise Performance

This plot shows the MSE for each embedding dimension:
- Lower bars indicate better predictions
- Variations show which dimensions are harder to predict
- Can guide targeted improvements
## Usage
```python
import skops.io as sio
# Load the model
model = sio.load('weight_predictor_ridge.skops')
# Make predictions
weights = model.predict(question_embedding)
```
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