Boosting Classification (OpenCV)
imagery_opencv
ParameterMultipleInput|FEATURES|Features|3|False
ParameterBoolean|NORMALIZE|Normalize|False
ParameterVector|TRAIN_AREAS|Training Areas|-1|False
ParameterTable|TRAIN_CLASS|Class Identifier|False
OutputRaster|CLASSES|Classification
QgsProcessingParameterNumber|MAX_DEPTH|Maximum Tree Depth|QgsProcessingParameterNumber.Integer|10|False| 1|None
QgsProcessingParameterNumber|MIN_SAMPLES|Minimum Sample Count|QgsProcessingParameterNumber.Integer|2|False| 2|None
QgsProcessingParameterNumber|MAX_CATEGRS|Maximum Categories|QgsProcessingParameterNumber.Integer|10|False| 1|None
ParameterBoolean|1SE_RULE|Use 1SE Rule|True
ParameterBoolean|TRUNC_PRUNED|Truncate Pruned Trees|True
QgsProcessingParameterNumber|REG_ACCURACY|Regression Accuracy|QgsProcessingParameterNumber.Double|0.010000|False| 0.000000|None
QgsProcessingParameterNumber|WEAK_COUNT|Weak Count|QgsProcessingParameterNumber.Integer|100|False| 0|None
QgsProcessingParameterNumber|WGT_TRIM_RATE|Weight Trim Rate|QgsProcessingParameterNumber.Double|0.950000|False| 0.000000| 1.000000
ParameterSelection|BOOST_TYPE|Boost Type|[0] Discrete AdaBoost;[1] Real AdaBoost;[2] LogitBoost;[3] Gentle AdaBoost| 1