Graphically explores the relationships between the training data and the predictor rasters.
● Data Source:
CranContrib
● Keywords: models
● Alias: model.explore
●
0 images
|
build.rastLUT
(Package: ModelMap) :
Build a raster Look-UP-Table for training dataset
GUI prompts will help the user build a Look-Up-Table to associated predictor variable with their corresponding spatial rasters.
● Data Source:
CranContrib
● Keywords: models
● Alias: build.rastLUT
●
0 images
|
Creates sophisticated models of training data and validates the models with an independent test set, cross validation, or in the case of Random Forest Models, with Out Of Bag (OOB) predictions on the training data. Create graphs and tables of the model validation results. Applies these models to GIS .img files of predictors to create detailed prediction surfaces. Handles large predictor files for map making, by reading in the .img files in chunks, and output to the .txt file the prediction for each data chunk, before reading the next chunk of data.
● Data Source:
CranContrib
● Keywords: package
● Alias: ModelMap, ModelMap-package
●
0 images
|
Internal Subfunctions
● Data Source:
CranContrib
● Keywords: internal
● Alias: initialize.device
●
0 images
|
get.test
(Package: ModelMap) :
Randomly Divide Data into Training and Test Sets
Uses random selection to split a dataset into training and test data sets
● Data Source:
CranContrib
● Keywords: models
● Alias: get.test
●
0 images
|
Takes model object and makes predictions, runs model diagnostics, and creates graphs and tables of the results.
● Data Source:
CranContrib
● Keywords: models
● Alias: model.diagnostics
●
0 images
|
Image or Perspective plot of two-way model interactions. Ranges of two specified predictor variables are plotted on X and Y axis, and fitted model values are plotted on the Z axis. The remaining predictor variables are fixed at their mean (for continuous predictors) or their most common value (for categorical predictors).
● Data Source:
CranContrib
● Keywords: models
● Alias: model.interaction.plot
●
0 images
|
Create sophisticated models using Random Forest, Quantile Regression Forests, Conditional Forests, or Stochastic Gradient Boosting from training data
● Data Source:
CranContrib
● Keywords: models
● Alias: model.build
●
0 images
|
Applies models to either ERDAS Imagine image (.img) files or ESRI Grids of predictors to create detailed prediction surfaces. It will handle large predictor files for map making, by reading in the .img files in rows, and output to the .img file the prediction for each data row, before reading the next row of data.
● Data Source:
CranContrib
● Keywords: models
● Alias: model.mapmake
●
0 images
|
col2trans
(Package: ModelMap) :
colors to transparent colors
transform color names to transparent versions of rgb color codes
● Data Source:
CranContrib
● Keywords: models
● Alias: col2trans
●
1 images
|