> For the complete documentation index, see [llms.txt](https://docs.exploratory.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.exploratory.io/machine-learning/prediction_coxph.md).

# Prediction - Survival Model

Predict with Survival Model.

## How to Access This Feature

### From + (plus) Button

From a step that creates a Survival Model, you can access this feature from 'Add' (Plus) button. Select one of the 3 "Predict" menus. ![](/files/-M4oNDvx_BBdJ5TUKuHR)

## How to Use This Feature

![](/files/-M4oNDvzYTALYfv_adUk)

1. With "Data" dropdown, select data to predict on from the following options.

* Training - Get predicted values on training data.
* Test - Get predicted values on test data.
* Data Frame - Get predicted values on other data frame.

1. Select "Type of Prediction" from the following options.

* Linear Predictor - lp - Risk Score on a log scale.
* Risk Score - exp(lp) - Score for the risk that the event happens within a unit time for the subject.
* Expected Number of Events - Number of events that would happen on average for a subject that has same condition as the subject during the time the subject has survived.
* Status at Specified Time - Predicted status of the subject at the specified time.

1. Select "Type of Residual" from the following options.

* Martingale
* Deviance
* Score
* Schoenfeld
* Schoenfeld (Scaled)
* DFBETA
* DFBETA (Scaled)

1. Click "Run" button to run the prediction.