nbsvm/nbsvm.py
def predict_proba(self, X):
        "Perform classification on samples in X and return class-wise probability scores"
        if not self.probability:
            raise ValueError("probabilty was set to False")
        else:
            dec_fn = self.decision_function(X)
            return self.platt_model_['model'].predict(dec_fn)
Perform classification on samples in X and return class-wise probability scores
Perform classification on samples in X and return class-wise probability scores
Perform classification on samples in X and return class - wise probability scores
def predict_proba(self, X):
        if not self.probability:
            raise ValueError("probabilty was set to False")
        else:
            dec_fn = self.decision_function(X)
            return self.platt_model_['model'].predict(dec_fn)
def predict_proba ( self , X ) : if not self . probability : raise ValueError ( "probabilty was set to False" ) else : dec_fn = self . decision_function ( X ) return self . platt_model_ [ 'model' ] . predict ( dec_fn )
Perform classification on samples in X and return class-wise probability scores
Perform classification on samples in X and return class - wise probability scores
"Perform classification on samples in X and return class-wise probability scores"
self
X