def build_shotclasstable(cross=True):
from db.prozoneDB import DB
c = DB.c
conn = DB.conn
idsX = np.array(get_features(["shotid"] + f,wo_penalties,only_fcb_shots))
X = idsX[:,1:]
y = np.array(get_results(wo_penalties,only_fcb_shots))
if cross:
prob = model.crosspredict(X,y)
else:
model.fit(X,y)
prob = model.predict(X)
#print prob
c.execute("drop table if exists Shotvalue")
c.execute("create table Shotvalue (shotid int,esv real)")
for t in zip(idsX[:,0],prob):
print(t)
c.execute("insert into Shotvalue values (?,?)",t)
conn.commit()
conn.close()
print("Shotclass table succcesfully built")
print_scores(get_scores(y,prob))
plot_roc_curve(y,prob)
def comparemodels(cross=True):
X = np.array(get_features(f,wo_penalties,only_fcb_shots))
X_alt = np.array(get_features(f_alt,wo_penalties,only_fcb_shots))
y = np.array(get_results(wo_penalties,only_fcb_shots))
if cross:
prob = model.crosspredict(X,y)
prob_alt = model_alt.crosspredict(X_alt,y)
else:
model.fit(X,y)
model_alt.fit(X,y)
prob = model.predict(X)
prob_alt = model.predict(X)
#compare_models(X, y, prob, prob_alt, f, f_plot=True)
plot_roc_curve(y, prob, prob_alt)
def analyze_model(cross=True):
X = np.array(get_features(f,wo_penalties,only_fcb_shots))
y = np.array(get_results(wo_penalties,only_fcb_shots))
if cross:
prob = model.crosspredict(X,y)
else:
model.fit(X,y)
prob = model.predict(X)
# print prob
# plt.hist(prob)
# plt.show()
#plot_model_analysis(X,y,prob,f)
print_scores(get_scores(y,prob))
plot_roc_curve(y,prob)
