TauVsDIS_MachineLearning_Differentiation.py File Reference

Go to the source code of this file.

Namespaces
namespace	TauVsDIS_MachineLearning_Differentiation

Variables
string	TauVsDIS_MachineLearning_Differentiation.path "./data/JetSummary_p250_e20_1000events_r05.csv"
list	TauVsDIS_MachineLearning_Differentiation.names ['n_track','charge_tot','eta','vertex','class']
tuple	TauVsDIS_MachineLearning_Differentiation.dataset pandas.read_csv(path, names=names)
	TauVsDIS_MachineLearning_Differentiation.array dataset.values
list	TauVsDIS_MachineLearning_Differentiation.X array[:,0:4]
list	TauVsDIS_MachineLearning_Differentiation.Y array[:,4]
float	TauVsDIS_MachineLearning_Differentiation.validation_size 0.60
int	TauVsDIS_MachineLearning_Differentiation.seed 7
tuple	TauVsDIS_MachineLearning_Differentiation.ding np.column_stack((X_train,Y_train))
tuple	TauVsDIS_MachineLearning_Differentiation.dong np.column_stack((X_validation,Y_validation))
string	TauVsDIS_MachineLearning_Differentiation.scoring 'accuracy'
list	TauVsDIS_MachineLearning_Differentiation.models []
list	TauVsDIS_MachineLearning_Differentiation.results []
tuple	TauVsDIS_MachineLearning_Differentiation.kfold model_selection.KFold(n_splits=10, random_state=seed)
tuple	TauVsDIS_MachineLearning_Differentiation.cv_results model_selection.cross_val_score(model, X_train, Y_train, cv=kfold, scoring=scoring)
string	TauVsDIS_MachineLearning_Differentiation.msg "%s: %f (%f)"
tuple	TauVsDIS_MachineLearning_Differentiation.ada AdaBoostClassifier()
tuple	TauVsDIS_MachineLearning_Differentiation.predictions ada.predict(X_validation)