Model run with party package:

Executing (Fit Random Forest Model): RandomForestModelFitToArcGISTable Z:\sharks\Models\Summer2013\summer2013.gdb\bll_llc_simple Z:\sharks\Models\Summer2013\RF\ALL\SB_RF\del\AR_del\ALL_SBRF_AR_del.Rdata "factor(Sandbar_Presence) ~ GSM_Chl_Daily_MF + SST_PF_daily+ Dist2Shr+DaylightHours+ Bathy2 + Slope + MoonPhase + factor(Region)" 500 # party # false # 25 false false false # # # # false false false png 1000 3000 3000 10 white
Start Time: Mon Dec 02 15:13:10 2013
Running script RandomForestModelFitToArcGISTable...
Querying ArcGIS table "Z:\sharks\Models\Summer2013\summer2013.gdb\bll_llc_simple".
Finished retrieving points: 0:00:00 elapsed, 1428 points retrieved, 0:00:00.000283 per point.
Fitting the random forest using the party package.

MODEL SUMMARY:
==============

	 Random Forest using Conditional Inference Trees

Number of trees:  500

Response:  factor(Sandbar_Presence)
Inputs:  GSM_Chl_Daily_MF, SST_PF_daily, Dist2Shr, DaylightHours, Bathy2, Slope, MoonPhase, factor(factor(Region), levels = c("1", "2", "3", "4", "5", "6"))
Number of observations:  534

Random number generator seed: 25
Number of variables tried at each split: 5

Completed script RandomForestModelFitToArcGISTable...
Succeeded at Mon Dec 02 15:13:26 2013 (Elapsed Time: 16.00 seconds)
Executing (Predict Random Forest From Rasters): RandomForestModelPredictFromArcGISRasters Z:\sharks\Models\Summer2013\RF\ALL\SB_RF\del\AR_del\ALL_SBRF_AR_del.Rdata Z:\sharks\Models\Summer2013\RF\ALL\SB_RF\AVpresPPdh6SS\AR_AVpresPPdh6SS\outputRasters\test bathy.img Slope;SST_PF_daily;GSM_Chl_Daily_MF;Dist2Shr;Bathy2;Region Z:\sharks\Models\Summer2013\environmentalrasters\Slope.img;Z:\sharks\Models\Summer2013\Data_From_Jason\2005chlasst_clipped\sst_gaussian_2005365.img;Z:\sharks\Models\Summer2013\Data_From_Jason\2005chlasst_clipped\GSMChl_gaussian_2005001.img;Z:\sharks\Models\Summer2013\environmentalrasters\Dist2Shr.img;Z:\sharks\Models\Summer2013\environmentalrasters\bathy.img;Z:\sharks\Models\Summer2013\environmentalrasters\divisions_updated.img MoonPhase;DaylightHours 0.994603;.45 # # true false
Start Time: Mon Dec 02 15:13:26 2013
Running script RandomForestModelPredictFromArcGISRasters...
Warning: package 'rgdal' was built under R version 2.15.2
Warning: package 'sp' was built under R version 2.15.2
Loaded RandomForest from Z:\sharks\Models\Summer2013\RF\ALL\SB_RF\del\AR_del\ALL_SBRF_AR_del.Rdata. The model was fitted with the R party package.
Checking coordinate systems, extents, and cell sizes of predictor rasters and reprojecting and clipping as needed to make them conform to the template raster...
Projecting and clipping Z:\sharks\Models\Summer2013\environmentalrasters\divisions_updated.img. Its coordinate system does not match that of the template raster.
Predicting...
Warning: This appears to be a binary classification model but no cutoff value was provided. The output will be a continuous floating-point value ranging from 0 to 1. To obtain a binary integer value, please provide a cutoff and try again.
RPy_RException: Error in checkData(oldData, RET) : 
  Classes of new data do not match original data
Obtaining additional debugging information. This may cause this tool to hang. If you do not see any additional messages after one minute, halt its execution.

Traceback (most recent call last):
  File "C:\Python27\ArcGIS10.1\Lib\site-packages\GeoEco\ArcGISToolbox\Scripts\RandomForestModelPredictFromArcGISRasters.py", line 5, in <module>
    ExecuteMethodFromCommandLineAsArcGISTool('GeoEco.Statistics.Modeling', 'RandomForestModel', 'PredictFromArcGISRasters')
  File "C:\Python27\ArcGIS10.1\lib\site-packages\GeoEco\ArcGISScripts.py", line 210, in ExecuteMethodFromCommandLineAsArcGISTool
    exec sourceCode in globals(), locals()
  File "<string>", line 1, in <module>
  File "C:\Python27\ArcGIS10.1\lib\site-packages\GeoEco\Statistics\Modeling.py", line 717, in PredictFromArcGISRasters
    _PredictFromArcGISRasters('randomForest', _(u'Fit Random Forest Model'), inputModelFile, outputResponseRaster, cutoff, constantPredictorNames, constantPredictorValues, rasterPredictorNames, predictorRasters, templateRaster, resamplingTechniques, ignoreOutOfRangeValues, None, buildPyramids, overwriteExisting)
  File "C:\Python27\ArcGIS10.1\lib\site-packages\GeoEco\Statistics\Modeling.py", line 1482, in _PredictFromArcGISRasters
    r('PredictModelForArcGISRasters(model, modelMetadata, rastersForPredictors, constantsForPredictors, "%s", ignoreOutOfRangeValues=%s, cutoff=%s)' % (tempResponseFile.replace('\\', '\\\\'), str(ignoreOutOfRangeValues).upper(), cutoff))
  File "C:\Python27\ArcGIS10.1\lib\site-packages\GeoEco\R.py", line 1066, in __call__
    value = self._Object(str(statements))
  File "C:\Python27\ArcGIS10.1\lib\site-packages\GeoEco\AssimilatedModules\rpy\rpy.py", line 339, in __call__
    return self.eval(self.parse(text=s))
RPy_RException: Error in checkData(oldData, RET) : 
  Classes of new data do not match original data

Failed to execute (Predict Random Forest From Rasters).
Failed at Mon Dec 02 15:14:01 2013 (Elapsed Time: 35.00 seconds)

Model run with randomForest package:

Executing (Fit Random Forest Model): RandomForestModelFitToArcGISTable Z:\sharks\Models\Summer2013\summer2013.gdb\bll_llc_simple Z:\sharks\Models\Summer2013\RF\ALL\SB_RF\del\AR_del\ALL_SBRF_AR_del.Rdata "factor(Sandbar_Presence) ~ GSM_Chl_Daily_MF + SST_PF_daily+ Dist2Shr+DaylightHours+ Bathy2 + Slope + MoonPhase + factor(Region)" 500 # randomForest # false # 25 false false false # # # # false false false png 1000 3000 3000 10 white
Start Time: Mon Dec 02 15:15:19 2013
Running script RandomForestModelFitToArcGISTable...
Querying ArcGIS table "Z:\sharks\Models\Summer2013\summer2013.gdb\bll_llc_simple".
Finished retrieving points: 0:00:00 elapsed, 1428 points retrieved, 0:00:00.000280 per point.
Fitting the random forest using the randomForest package.

MODEL SUMMARY:
==============

Call:
 randomForest(formula = factor(Sandbar_Presence) ~ GSM_Chl_Daily_MF + SST_PF_daily + Dist2Shr + DaylightHours + Bathy2 + Slope + MoonPhase + factor(factor(Region), levels = c("1", "2", "3", "4", "5", "6")),
 ntree = 500, replace = FALSE, importance = FALSE)

               Type of random forest: classification
                     Number of trees: 500
No. of variables tried at each split: 2

        OOB estimate of  error rate: 25.3%
Confusion matrix:
   0   1 class.error
0 88 104      0.5417
1 31 311      0.0906
Random number generator seed: 25

Completed script RandomForestModelFitToArcGISTable...
Succeeded at Mon Dec 02 15:15:33 2013 (Elapsed Time: 14.00 seconds)
Executing (Predict Random Forest From Rasters): RandomForestModelPredictFromArcGISRasters Z:\sharks\Models\Summer2013\RF\ALL\SB_RF\del\AR_del\ALL_SBRF_AR_del.Rdata Z:\sharks\Models\Summer2013\RF\ALL\SB_RF\AVpresPPdh6SS\AR_AVpresPPdh6SS\outputRasters\test bathy.img Slope;SST_PF_daily;GSM_Chl_Daily_MF;Dist2Shr;Bathy2;Region Z:\sharks\Models\Summer2013\environmentalrasters\Slope.img;Z:\sharks\Models\Summer2013\Data_From_Jason\2005chlasst_clipped\sst_gaussian_2005365.img;Z:\sharks\Models\Summer2013\Data_From_Jason\2005chlasst_clipped\GSMChl_gaussian_2005001.img;Z:\sharks\Models\Summer2013\environmentalrasters\Dist2Shr.img;Z:\sharks\Models\Summer2013\environmentalrasters\bathy.img;Z:\sharks\Models\Summer2013\environmentalrasters\divisions_updated.img MoonPhase;DaylightHours 0.994603;.45 # # true false
Start Time: Mon Dec 02 15:15:33 2013
Running script RandomForestModelPredictFromArcGISRasters...
Loaded randomForest.formula from Z:\sharks\Models\Summer2013\RF\ALL\SB_RF\del\AR_del\ALL_SBRF_AR_del.Rdata. The model was fitted with the R randomForest package.
Checking coordinate systems, extents, and cell sizes of predictor rasters and reprojecting and clipping as needed to make them conform to the template raster...
Projecting and clipping Z:\sharks\Models\Summer2013\environmentalrasters\divisions_updated.img. Its coordinate system does not match that of the template raster.
Predicting...
Warning: This appears to be a binary classification model but no cutoff value was provided. The output will be a continuous floating-point value ranging from 0 to 1. To obtain a binary integer value, please provide a cutoff and try again.
Creating outputs...
Completed script RandomForestModelPredictFromArcGISRasters...
Succeeded at Mon Dec 02 15:16:47 2013 (Elapsed Time: 1 minutes 14 seconds)