CODEWITHSUNDEEP
pythonpandasmachine-learningscikit-learnlinear-regression
Fring0.5
Fring0.5

Reputation: 3

Linar regression on pandas gives null as regression score

from sklearn.linear_model import LinearRegression

my_y = np.array([2, 5, 6, 10]).reshape(1, -1)
my_x = np.array([19, 23, 22, 30]).reshape(1,-1)

lm = LinearRegression()
lm = lm.fit(my_x, my_y)
result = lm.score(my_x, my_y)   
print(result)

Why does  this  give Nan as output

Upvotes: 0

Views: 42

Answers (1)

NYC Coder
NYC Coder

Reputation: 7594

You need to use reshape(-1, 1) for arrays

my_y = np.array([2,5,6,10]).reshape(-1, 1)
my_x = np.array([19,23,22,30]).reshape(-1, 1)

lm = sk.LinearRegression()
lm = lm.fit(my_x, my_y)
result = lm.score(my_x, my_y)
print(result)

0.9302407516147975

Upvotes: 1

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