CrossValidationResult
Summary
The CrossValidationResult class is returned by the Cross Validation tool and contains access to the cross-validation results that can be generated for any geostatistical layer.
Discussion
The CrossValidationResult class is similar to Result class except for the additional read-only properties that it contains. For detailed help, see the Cross Validation tool help.
Only the mean and root mean square error results are available for IDW, global polynomial interpolation, radial basis functions, diffusion interpolation with barriers, and kernel interpolation with barriers.
Properties
Property | Explanation | Data Type |
averageStandard (Read Only) |
The average of the prediction standard errors. | Double |
count (Read Only) |
The number of input samples. | Long |
inputCount (Read Only) |
Returns the number of inputs. | Integer |
maxSeverity (Read Only) |
Returns the maximum severity of the message. | Integer |
meanError (Read Only) |
The averaged difference between the measured and the predicted values. | Double |
meanStandardized (Read Only) |
Mean standardized error. | Double |
messageCount (Read Only) |
Returns the number of messages. | Integer |
outputCount (Read Only) |
Returns the number of outputs. | Integer |
resultID (Read Only) |
Gets the job ID. | String |
rootMeanSquare (Read Only) |
The root mean square error. | Double |
rootMeanSquareStandardized (Read Only) |
The root mean square standardized error should be close to 1 if the prediction standard errors are valid. If the root mean square standardized error is greater than 1, you are underestimating the variability in your predictions. If the root mean square standardized error is less than 1, you are overestimating the variability in your predictions. | Double |
status (Read Only) |
Gets the job status.
| Integer |
Method Overview
Method | Explanation |
cancel () |
Cancels an associated job |
getInput (index) |
Returns a given input, either as a recordset or string. |
getMapImageURL ({parameter_list}, {height}, {width}, {resolution}) |
Gets a map service image for a given output, if one exists. |
getMessage (index) |
Returns a specific message. |
getMessages ({severity}) |
Returns messages. |
getOutput (index) |
Returns a given output, either as a recordset or string. If the output of the tool, such as MakeFeatureLayer is a layer, getOutput will return a Layer object. |
getSeverity (index) |
Returns the severity of a specific message. |
Methods
Parameter | Explanation | Data Type |
index |
The index position of the input. | Integer |
Data Type | Explanation |
Object |
The input, either as a recordset or string. |
Parameter | Explanation | Data Type |
parameter_list (Optional) |
Parameter(s) on which the map service image will be based. | Integer |
height (Optional) |
The height of the image. | Double |
width (Optional) |
The width of the image. | Double |
resolution (Optional) |
The resolution of the image. | Double |
Data Type | Explanation |
String |
The URL of the map image. |
Parameter | Explanation | Data Type |
index |
The index position of the message. | Integer |
Data Type | Explanation |
String |
The geoprocessing message. |
Parameter | Explanation | Data Type |
severity (Optional) |
The type of messages to be returned: 0=message, 1=warning, 2=error. Not specifying a value returns all message types.
(The default value is 0) | Integer |
Data Type | Explanation |
String |
The geoprocessing messages. |
Parameter | Explanation | Data Type |
index |
The index position of the outputs. | Integer |
Data Type | Explanation |
Object |
The output, either as a recordset or string. If the output of the tool, such as MakeFeatureLayer is a layer, getOutput will return a Layer object. |
Parameter | Explanation | Data Type |
index |
The message index position. | Integer |
Data Type | Explanation |
Integer |
The severity of the specific message.
|
Code Sample
Perform cross-validation on an input geostatistical layer.
import arcpy arcpy.env.workspace = "C:/gapyexamples/data" cvResult = arcpy.CrossValidation_ga("C:/gapyexamples/data/kriging.lyr") print "Root Mean Square error = " + str(cvResult.rootMeanSquare)
Perform cross-validation on an input geostatistical layer.
# Name: CrossValidation_Example_02.py # Description: Perform cross validation on an input geostatistical layer. # Requirements: Geostatistical Analyst Extension # Author: ESRI # Import system modules import arcpy # Set environment settings arcpy.env.workspace = "C:/gapyexamples/data" # Set local variables inLayer = "C:/gapyexamples/data/kriging.lyr" # Check out the ArcGIS Geostatistical Analyst extension license arcpy.CheckOutExtension("GeoStats") # Execute CrossValidation cvResult = arcpy.CrossValidation_ga(inLayer) print "Root Mean Square error = " + str(cvResult.rootMeanSquare)