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Ensembles allow the user to combine models and heuristics into a single ensemble that returns a single output. Ensembles can contain any combination of heuristics, classical models, and neural models.

<aside> <img src="https://s3-us-west-2.amazonaws.com/secure.notion-static.com/52e85db3-0847-4231-a3ed-8afc6f2124ba/0_JAXON_Logo_Mark.jpg" alt="https://s3-us-west-2.amazonaws.com/secure.notion-static.com/52e85db3-0847-4231-a3ed-8afc6f2124ba/0_JAXON_Logo_Mark.jpg" width="40px" /> Ensembles must be composed of at least one model or heuristic.

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On this page you will find:

• How to Create a New Ensemble
• Example Ensemble Overview
• How to Label a Dataset Using an Ensemble
• How to Delete an Ensemble

How to Create a New Ensemble

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1. To create a new ensemble, select  +  from the Ensembles Menu

• Ensemble Training Form Field Descriptions

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Ensemble creation is asynchronous - once the job is submitted, users may close the browser window and return later to check the job status. Users may submit multiple such jobs, and each job will run in the order in which they are submitted. Ensemble creation may take a few minutes, or up to several hours.

1. Fill out the ensemble training form and select Submit

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Example Ensemble Overview

Here, Jaxon provides valuable information about ensemble training and accuracy. Selecting an ensemble will bring up a confusion matrix for that ensemble and the option to label a dataset using the created ensemble.

A table is included that contains a breakdown of the Aggregator used to create the ensemble as well the ensemble’s F-Score, Precision, Recall, and Coverage.

The overview provides a Confusion Matrix that maps out the predicted vs actual accuracy of the classifier for the given examples.

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Hovering over one of the cells within the confusion matrix will bring up the number of examples that were expected to fall into that cell (Predicted) vs the number of examples that actually fell within that cell (Actual).

The hover box provided for the top left cell of the confusion matrix.

Clicking one of the cells within the confusion matrix will bring up actual examples that fell into that cell. This can be used for further calibration to see why certain mistakes happened and strategize how to resolve said mistakes.

The examples shown that fell into the top left cell of the confusion matrix.

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How to Label a Dataset Using an Ensemble

Once an ensemble has been created, it can be used to label any available datasets already in the Datasets tab.

1. To view all available ensembles within the Ensemble tab, select 🔽

1. Select the ensemble you want to use to label a dataset. When an ensemble is successfully selected, the list of ensembles disappears and only information about that ensemble is shown.

1. Fill out the information in the Label Dataset box

• Label Dataset box Field Descriptions

<aside> <img src="https://s3-us-west-2.amazonaws.com/secure.notion-static.com/be9de3a4-618e-4323-a905-2bda3ce66a80/0_JAXON_Logo_Mark_2.jpg" alt="https://s3-us-west-2.amazonaws.com/secure.notion-static.com/be9de3a4-618e-4323-a905-2bda3ce66a80/0_JAXON_Logo_Mark_2.jpg" width="40px" /> Once a dataset has been labeled by a Jaxon ensemble, the newly-labeled dataset will be available in the Datasets tab.

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1. Once the user selects Label there is the option to only label the dataset, or to also automatically have it download after the labeling has completed.

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How to Delete an Ensemble

Once an ensemble has been created, it can be deleted. Ensemble deletion cannot be undone.

1. To view all available ensembles within the Ensembles tab, select 🔽

1. Select the Delete Ensemble icon if you really want to delete the ensemble. We cannot stress enough that this action cannot be undone.

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