Using Classification
The Classification feature allows users to categorise dataset rows by applying labels based on text content from a selected column. Using a pre-trained AI model, the system assigns the most relevant classification label to each row, storing the results in a new column.
1. Select a Dataset
Before setting up classification, ensure you have selected a dataset. If no dataset is available, follow the steps to Add Dataset on the Future AGI platform.
2. Accessing the Classification Interface
To configure classification, navigate to your dataset and click the + Add Columns button in the top-right menu. Scroll down to the Dynamic Columns section and select Classification to open the setup panel.
3. Configuring Classification Settings
- Name: Assign a name to the new column where the classification results will be stored.
- Column: Select the dataset column that contains text data to be classified.
- Labels: Manually define classification labels by clicking Add Label. These labels should represent the possible categories for classification.
- Example: If it is product reviews, you can set labels as “Positive”, “Negative”, and “Neutral”.
- Model: Choose an AI model that will process the classification task.
- Concurrency: Define how many rows should be processed simultaneously for efficiency.
After configuring the settings, click Test to preview classification results on sample rows. If the classifications appear accurate, click Create New Column to apply classification across the dataset.
The new column will populate with predicted labels for each row based on the selected AI model.
Best Practices for Using Classification
- Ensure the selected column contains meaningful text data for classification.
- Define clear and distinct labels to improve the accuracy of classification.
- Adjust concurrency settings based on dataset size for better processing efficiency.