Below is my trial code:
from sklearn import linear_model
# plt.title("Time-independent variant student performance analysis")
x_train = [5, 9, 33, 25, 4]
y_train = [35, 2, 14 ,9, 7]
x_test = [14, 2, 8, 1, 11]
# create linear regression object
linear = linear_model.LinearRegression()
#train the model using the training sets and check score
linear.fit(x_train, y_train)
linear.score(x_train, y_train)
# predict output
predicted = linear.predict(x_test)
when run, this is the output:
ValueError: Found arrays with inconsistent numbers of samples: [1 5]
Redefine
x_train = [[5],[9],[33],[25],[4]]
y_train = [35,2,14,9,7]
x_test = [[14],[2],[8],[1],[11]]
From doc of fit(X, y)
: X
: numpy array or sparse matrix of shape [n_samples,n_features]
In your case, every example has only one feature.
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