In [2]:

    

from sklearn.preprocessing import PolynomialFeatures
from sklearn import linear_model
import matplotlib.pyplot as plt 

X = [[0.44, 0.68], [0.99, 0.23]]
vector = [109.85, 155.72]
predict= [[0.49, 0.18], [0.47, 0.22]]

poly = PolynomialFeatures(degree=2)
X_ = poly.fit_transform(X)
predict_ = poly.fit_transform(predict)

clf = linear_model.LinearRegression()
clf.fit(X_, vector)
y=clf.predict(predict_)
print (clf.predict(predict_))


    

    




[ 126.84247142  125.01176842]

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