# Enter your code here. Read input from STDIN. Print output to STDOUT
from sklearn.linear_model import LinearRegression
from sklearn.preprocessing import PolynomialFeatures

F,N= map(int ,input().split())
x=[]
y=[]

for _ in range(N):
    data=list(map(float ,input().split()))
    x.append(data[:-1])
    y.append(data[-1])
    
    
T=int(input())
x_test=[]
for _ in range(T):
    data=list(map(float ,input().split()))
    x_test.append(data)
    
poly = PolynomialFeatures(degree=3)

xpoly=poly.fit_transform(x)
x_testpoly=poly.transform(x_test)

model =LinearRegression()
model.fit(xpoly,y)

predicted=model.predict(x_testpoly)

for p in predicted:
    print(str(round(p,2)))