ml - Weighted Random Forest

None

Paramètres

ListOf_Input_Features_Image: ListOf( Volume 3D ) ( input )

ListOf_Input_Segmented_Image: ListOf( Graph ) ( input )

Input_Feature_Description: Text file ( optional, entrée )

Classes_Weights: ListOf( Réel ) ( optional, input )

Max_Depth: Entier ( optional, input )

N_Trees: Entier ( input )

Output_Model: Any Type ( sortie )

Informations techniques

Toolbox : Bioprocessing

Niveau d'utilisateur : 3

Identifiant : ml_RandomForest

Nom de fichier : brainvisa/toolboxes/bioprocessing/processes/research/toolbox/machine_learning/ml_toolbox/ml_RandomForest.py

Supported file formats :

ListOf_Input_Features_Image :

gz compressed NIFTI-1 image, Aperio svs, BMP image, DICOM image, Directory, ECAT i image, ECAT v image, FDF image, FreesurferMGH, FreesurferMGZ, GIF image, GIS image, Hamamatsu ndpi, Hamamatsu vms, Hamamatsu vmu, JPEG image, Leica scn, MINC image, NIFTI-1 image, PBM image, PGM image, PNG image, PPM image, SPM image, Sakura svslide, TIFF image, TIFF image, TIFF(.tif) image, TIFF(.tif) image, VIDA image, Ventana bif, XBM image, XPM image, Zeiss czi, gz compressed MINC image, gz compressed NIFTI-1 image

ListOf_Input_Segmented_Image :

Graph and data, Graph and data

Input_Feature_Description :

Text file, Text file

Output_Model :

pickle file, pickle file