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))