def knn3(d,v):
return num.knnestimate(d,v,k=3)
def knn1(d,v):
return num.knnestimate(d,v,k=1)
import colint.chapter8.numpredict as num
print(num.wineprice(95.0, 3.0))
# Generate dataset containing prices of various wines of different raing and age
# data is a list of 'input' => rating, age, 'result' => price
data = num.wineset1()
print(data)
print(num.knnestimate(data, (99.0, 3.0)))
print("Reale price: %s" % num.wineprice(99.0, 5.0))
print("Estimated price (5 noughbours) %s" % num.knnestimate(data, (99.0, 5.0), k=5))
print("Estimated price (2 noughbours) %s" % num.knnestimate(data, (99.0, 5.0), k=1))
print("Weighted knn %s" % num.weightedknn(data, (99.0, 5.0)))
print(num.crossvalidate(num.knnestimate, data))
def knn3(d,v):
return num.knnestimate(d,v,k=3)
def knn1(d,v):
return num.knnestimate(d,v,k=1)
print(num.crossvalidate(knn3, data))
print(num.crossvalidate(knn1, data))
