Unsupervised Classification

Description

Unsupervised classification by kmeans, Clustering for Large Applications (CLARA) and Random Forest

Name	Type	Description
Input Folder	Folder	Folder with predictors raster files (variables) in geoTif format
Number Of Classes	Real Value Type	Number of classes in classification
kmeans	Boolean	Project PLSR in another scenario (future or past)
Clara	Boolean	Project PLSR in another scenario (future or past)
Random Forest	Boolean	Project PLSR in another scenario (future or past)
Output kmeans	Boolean	Output raster of k-means classification
Output Clara	Boolean	Output raster of clara classification
Output Random Forest	Boolean	Output raster of Random Forest classification
Number Of Interactions	Real Value Type	Maximum number of interactions in k-means classification
Start Random Sets	Real Value Type	Number of start random sets
Sample Size In Clara	Real Value Type	Sample Size In Clara classification
Distance Metric In Clara	Real Value Type	1 - euclidean; 2 - manhattan;
Sample Size In Random Forest	Real Value Type	Sample Size In Random Forest classification
Number Of Trees	Real Value Type	Number of trees in Random Forest

Name	Type	Description
Output kmeans	string	Output raster filename of k-means classification
Output Clara	string	Output raster filename of clara classification
Output Random Forest	string	Output filename raster of Random Forest classification

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