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src/a/z/AZOrange-HEAD/azorange/AZLearnersParamsConfig.py   AZOrange(Download)
"""
CvBoostLearner = {
             'max_depth':["types.IntType", "values", "[int(round(x)) or 1 for x in miscUtilities.Range(1,20)]",[],AZOrangeConfig.CVBOOSTDEFAULTDICT["max_depth"],True,True,"Integer from 1 to 20.\nMinimum is 1"],\
             'weak_count':["types.IntType", "values", "miscUtilities.Range(1,1000)",[],AZOrangeConfig.CVBOOSTDEFAULTDICT["weak_count"],False,True,"Integer from 1 to 1000"],\
             'weight_trim_rate':["types.FloatType", "interval", "[0 , 1]",[],AZOrangeConfig.CVBOOSTDEFAULTDICT["weight_trim_rate"],False,True,"Continious between"],\
             'boost_type':["types.StringType", "values", "['DISCRETE' , 'REAL' , 'LOGIT' , 'GENTLE']",['DISCRETE','REAL','LOGIT','GENTLE'],AZOrangeConfig.CVBOOSTDEFAULTDICT["boost_type"],False,False,"DISCRETE\nREAL\nLOGIT\nGENTLE"],\
             'split_criteria':["types.StringType", "values", "['DEFAULT' , 'GINI' , 'MISCLASS' , 'SQERR']",['DEFAULT' , 'GINI' , 'MISCLASS' , 'SQERR'],AZOrangeConfig.CVBOOSTDEFAULTDICT["split_criteria"],False,False,"DEFAULT\nGINI\nMISCLASS\nSQERR"],\

src/a/z/AZOrange-HEAD/azorange/trainingMethods/AZorngCvBoost.py   AZOrange(Download)
 
        for par in ("boost_type","weak_count","split_criteria","weight_trim_rate", "max_depth", "use_surrogates","priors"): 
            setattr(self, par, AZOC.CVBOOSTDEFAULTDICT[par])
        self.__dict__.update(kwds)
 

src/a/z/AZOrange-HEAD/orange/OrangeWidgets/Classify/OWCvBoost.py   AZOrange(Download)
        #CVBOOSTDEFAULTDICT = {"boost_type":"DISCRETE","weak_count":100,"split_criteria":"DEFAULT","weight_trim_rate":0.95, "max_depth":1, "use_surrogates":True, "priors":None}
        for par in ("boost_type","weak_count","split_criteria","weight_trim_rate", "max_depth", "use_surrogates","priors"):
            setattr(self, par, AZOC.CVBOOSTDEFAULTDICT[par])
 
        self.data = None                    # input data set