value error found with inconsistent samples

Question

x_forecast = x[-forecast_out:]

x = x[:-forecast_out]

y = np.array(df['prediction'])

y = y[:-forecast_out]

x_train, x_test, y_train, y_test = train_test_split(x, y, test_size=0.2, random_state = 0)

clf = LinearRegressio()

clf.fit(train_x, train_y)

s = clf.score(test_x, test_y)

print('score', s)

error:

ValueError                                Traceback (most recent call last)

<ipython-input-80-7476b5a54000> in <module>()
----> 1 x_train, x_test, y_train, y_test = train_test_split(x, y, test_size=0.2, random_state = 0)
      2 
      3 clf = LinearRegressio()
      4 clf.fit(train_x, train_y)
      5 

---

2 frames

---

/usr/local/lib/python3.6/dist-packages/sklearn/utils/validation.py in check_consistent_length(*arrays)
    210     if len(uniques) > 1:
    211         raise ValueError("Found input variables with inconsistent numbers of"
--> 212                          " samples: %r" % [int(l) for l in lengths])
    213 
    214 

ValueError: Found input variables with inconsistent numbers of samples: [1417, 1477]

Answer 1

Hi,

As you can see that you have an inconsistent number of samples in x and y. Before you create your model, you need to check the shape of the x and y variables. These two variables should have the same number of rows and y should be two dimensional.