# Clustering

**`Select the appropriate model`** : you can choose from a list of all models generated from Build and Evaluate part:

* Model trained with custom number of clusters
* Model trained using Elbow method
* Model trained and tuned with data containing labled target
* Pre-existing model

If you choose **pre-existing model**, then you need to enter the name of the model without .pkl extention.

Now you either choose to make prediction for a single observation, which means you have one instance and you want to predict the target, in this case you need to fill manually all the features of that instance, check your entries if they are correct, and click predict, or if you want to predict multiple observations, in this case you need to drag and drop your file that contains observations you want to predict, the file must be a csv or exel file. Click **`Predict`** button:

![Predicting single observation cluster.](https://1577378233-files.gitbook.io/~/files/v0/b/gitbook-legacy-files/o/assets%2F-MT0DqusrMJSGtXvrnXz%2F-MVka5QubGcspisL6mF8%2F-MVkfMTO7z8rYUKciB5Q%2Fimage.png?alt=media\&token=41bac1dd-fb18-4c07-8b73-09025dcd4ed3)

![Predicting clusters for multiple observation ](https://1577378233-files.gitbook.io/~/files/v0/b/gitbook-legacy-files/o/assets%2F-MT0DqusrMJSGtXvrnXz%2F-MVka5QubGcspisL6mF8%2F-MVkfhTHMSVrxpkppHPC%2Fimage.png?alt=media\&token=ac0810a2-0061-43db-883c-23f31a674660)

{% hint style="info" %}
Clustered data will be saved under the file name predicted\_data\_13.csv where 13 is your session ID.
{% endhint %}
