> For the complete documentation index, see [llms.txt](https://docs.graphite-note.com/graphite-note-documentation/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.graphite-note.com/graphite-note-documentation/~/changes/E2AMshWWxt1bMPRlFt2a/models/predict-with-ml-models.md).
# Predict with ML Models
The "Predict Dataset" functionality in Graphite Note allows users to apply a successfully trained and deployed model to a specific dataset for generating predictions. This section provides a comprehensive guide on how to utilize this feature to make informed decisions.
### **Overview**
Once a model has been trained and deployed within Graphite Note, it can be used to make predictions on a specific dataset. The dataset must have the same structure (columns) as the one the model was trained on. Graphite Note will add new columns to the dataset containing the model's predictions and scores for each row.
### **How to Use the Predict Dataset Feature**
1. **Select Dataset to Predict**:
* Navigate to the "Predict Dataset" section.
* Choose the specific dataset you want to apply the model to. This dataset must have the same columns that the model was trained on.
2. **Verify Dataset Structure**:
* Ensure that the selected dataset has the same structure (columns) as the trained model. This alignment is crucial for accurate predictions.
3. **Apply Model to Dataset**:
* Select Dataset by double click
* Graphite Note will add new columns to the selected dataset containing the model's predictions and scores for each row.
4. **Analyze Predictions**:
* View the results within Graphite Note's user-friendly interface.
* Analyze the predictions to understand trends, patterns, and insights that can guide decision-making.
5. **Make Decisions**:
* Utilize the predictions to make informed decisions aligned with your business goals and strategies.
6. **Export to Excel**:
* If desired, you can export the dataset with the added prediction columns to Excel for further analysis or sharing with stakeholders.
### **Key Considerations**
* **Column Alignment**: The selected dataset must have the same columns as the ones the model was trained on. Mismatched columns may lead to incorrect predictions.
* **Real-time Application**: Graphite Note's Predict Dataset feature provides real-time application of models to datasets, enabling quick insights.
* **Customizable Analysis**: Tailor the analysis of predictions within Graphite Note to suit your specific needs and preferences.
### **Conclusion**
The "Predict Dataset" feature in Graphite Note streamlines the process of applying trained models to specific datasets. By ensuring alignment between the model and dataset structure, users can generate accurate predictions that drive actionable insights.
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