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
ParameterNumber|MAX_DEPTH|Maximum Tree Depth| 1|None| 10
ParameterNumber|MIN_SAMPLES|Minimum Sample Count| 2|None| 2
ParameterNumber|MAX_CATEGRS|Maximum Categories| 1|None| 10
ParameterBoolean|1SE_RULE|Use 1SE Rule|True
ParameterBoolean|TRUNC_PRUNED|Truncate Pruned Trees|True
ParameterNumber|REG_ACCURACY|Regression Accuracy| 0.000000|None| 0.010000
ParameterNumber|WEAK_COUNT|Weak Count| 0|None| 100
ParameterNumber|WGT_TRIM_RATE|Weight Trim Rate| 0.000000| 1.000000| 0.950000
ParameterSelection|BOOST_TYPE|Boost Type|[0] Discrete AdaBoost;[1] Real AdaBoost;[2] LogitBoost;[3] Gentle AdaBoost| 1