Label | Explanation | Data Type |

Input Features | The point features that will be interpolated to a continuous surface layer. | Feature Set |

Output Name | The name of the output layer to create on your portal. | String |

Interpolation Field
(Optional) | The numeric field containing the values you want to interpolate. | Field |

Interpolate Option (Optional) | Controls your preference for speed versus accuracy, from fastest to most accurate. More accurate predictions take longer to calculate. - Speed —Speed.
- Balanced —Balanced. This is the default.
- Accuracy —Accuracy.
| String |

Output prediction error (Optional) | If checked, a polygon layer of standard errors for the interpolation predictions will be output. Standard errors are useful because they provide information about the reliability of the predicted values. A simple rule of thumb is that the true value will fall within two standard errors of the predicted value 95 percent of the time. For example, suppose a new location gets a predicted value of 50 with a standard error of 5. This means that this task's best guess is that the true value at that location is 50, but it reasonably could be as low as 40 or as high as 60. To calculate this range of reasonable values, multiply the standard error by 2, add this value to the predicted value to get the upper end of the range, and subtract it from the predicted value to get the lower end of the range. - Unchecked—Do not create a prediction error output layer. This is the default.
- Checked—Create a prediction error output layer.
| Boolean |

Classification Type (Optional) | Determines how predicted values will be classified into polygons. - Equal interval — Polygons are created such that the range of density values is equal for each area.
- Geometric interval — Polygons are based on class intervals that have a geometric series. This method ensures that each class range has approximately the same number of values within each class and that the change between intervals is consistent. This is the default.
- Equal area — Polygons are created such that the size of each area is equal. For example, if the result has more high-density values than low-density values, more polygons will be created for high densities.
- Enter class breaks manually —You define your own range of values for areas. These values will be entered as class breaks.
| String |

Number of Classes (Optional) | This value is used to divide the range of predicted values into distinct classes. The range of values in each class is determined by the classification type. Each class defines the boundaries of the result polygons. The default is 10 and the maximum is 32. | Long |

Class Breaks
(Optional) | To do a manual classification, supply the desired class break values. These values define the upper limit of each class, so the number of classes will equal the number of entered values. Areas will not be created for any locations with predicted values above the largest entered break value. You must enter at least 2 values and no more than 32. | Double |

Bounding Polygons
(Optional) | A layer specifying the polygons where you want values to be interpolated. For example, if you are interpolating densities of fish within a lake, you can use the boundary of the lake in this parameter and the output will only contain polygons within the boundary of the lake. | Feature Set |

Predict At Point Layer
(Optional) | An optional layer specifying point locations to calculate prediction values. This allows you to make predictions at specific locations of interest. For example, if the input layer represents measurements of pollution levels, you can use this parameter to predict the pollution levels of locations with large at-risk populations, such as schools or hospitals. You can then use this information to give recommendations to health officials in those locations. | Feature Set |

### Derived Output

Label | Explanation | Data Type |

Output Layer | The output polygon features, where each polygon surrounds interpolated values based on the classification type and number of classes. | Feature Set |

Output Prediction Error Layer | Contains the predicted error for each point in the input layer. | Feature Set |

Output Predicted Points Layer | The point layer containing points from the predicted point layer with their predicted values. | Feature Set |