You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
ciao,
seguendo il corso, una volta attivato a questo punto, from sklearn.preprocessing import PolynomialFeatures polyfeats = PolynomialFeatures(degree = 2) X_train_poly = polyfeats.fit_transform(X_train) X_test_poly = polyfeats.transform(X_test)
mi dà tale errore
`ValueError Traceback (most recent call last)
in
1 from sklearn.preprocessing import PolynomialFeatures
2 polyfeats = PolynomialFeatures(degree = 2)
----> 3 X_train_poly = polyfeats.fit_transform(X_train)
4 X_test_poly = polyfeats.transform(X_test)
~\Anaconda3\lib\site-packages\sklearn\base.py in fit_transform(self, X, y, **fit_params)
551 if y is None:
552 # fit method of arity 1 (unsupervised transformation)
--> 553 return self.fit(X, **fit_params).transform(X)
554 else:
555 # fit method of arity 2 (supervised transformation)
~\Anaconda3\lib\site-packages\sklearn\utils\validation.py in check_array(array, accept_sparse, accept_large_sparse, dtype, order, copy, force_all_finite, ensure_2d, allow_nd, ensure_min_samples, ensure_min_features, warn_on_dtype, estimator)
519 "Reshape your data either using array.reshape(-1, 1) if "
520 "your data has a single feature or array.reshape(1, -1) "
--> 521 "if it contains a single sample.".format(array))
522
523 # in the future np.flexible dtypes will be handled like object dtypes
ciao,
seguendo il corso, una volta attivato a questo punto,
from sklearn.preprocessing import PolynomialFeatures polyfeats = PolynomialFeatures(degree = 2) X_train_poly = polyfeats.fit_transform(X_train) X_test_poly = polyfeats.transform(X_test)
mi dà tale errore
`ValueError Traceback (most recent call last)
in
1 from sklearn.preprocessing import PolynomialFeatures
2 polyfeats = PolynomialFeatures(degree = 2)
----> 3 X_train_poly = polyfeats.fit_transform(X_train)
4 X_test_poly = polyfeats.transform(X_test)
~\Anaconda3\lib\site-packages\sklearn\base.py in fit_transform(self, X, y, **fit_params)
551 if y is None:
552 # fit method of arity 1 (unsupervised transformation)
--> 553 return self.fit(X, **fit_params).transform(X)
554 else:
555 # fit method of arity 2 (supervised transformation)
~\Anaconda3\lib\site-packages\sklearn\preprocessing\data.py in fit(self, X, y)
1463 self : instance
1464 """
-> 1465 n_samples, n_features = check_array(X, accept_sparse=True).shape
1466 combinations = self._combinations(n_features, self.degree,
1467 self.interaction_only,
~\Anaconda3\lib\site-packages\sklearn\utils\validation.py in check_array(array, accept_sparse, accept_large_sparse, dtype, order, copy, force_all_finite, ensure_2d, allow_nd, ensure_min_samples, ensure_min_features, warn_on_dtype, estimator)
519 "Reshape your data either using array.reshape(-1, 1) if "
520 "your data has a single feature or array.reshape(1, -1) "
--> 521 "if it contains a single sample.".format(array))
522
523 # in the future np.flexible dtypes will be handled like object dtypes
ValueError: Expected 2D array, got 1D array instead:
array=[34.41 7.73 16.96 4.97 17.93 18.72 13.09 21.02 26.45 10.26 4.59 5.25
8.05 12.79 7.7 7.22 7.79 16.35 4.38 24.91 14.65 5.5 13.34 21.78
15.1 21.14 11.66 9.43 16.23 14.52 9.8 11.64 18.66 5.08 9.5 5.99
4.45 16.22 23.98 11.25 5.7 11.5 3.16 6.21 9.5 14.13 5.98 3.01
8.16 11.69 7.26 6.62 27.8 6.43 14.1 5.9 10.58 12.14 6.53 9.54
18.05 10.24 11.72 24.08 24.16 7.67 15.17 4.03 20.08 21.46 14.67 16.65
9.25 13.27 22.6 10.45 6.36 13.44 19.01 7.9 10.11 3.53 12.04 11.1
19.52 14.37 8.1 16.21 5.29 6.36 10.29 16.9 5.1 5.49 9.45 27.26
7.85 20.34 34.37 21.24 17.16 2.47 15.03 18.35 7.01 9.55 14.44 4.56
6.59 9.51 17.92 7.54 9.68 23.79 11.98 7.12 10.53 16.94 9.69 17.28
21.32 6.27 16.14 9.74 23.6 21.32 16.03 12.33 8.05 5.98 5.57 9.47
22.88 5.39 29.55 2.88 8.05 6.9 8.1 16.3 13.51 7.6 18.34 10.16
3.7 14.1 29.97 1.98 3.53 14.19 9.1 18.33 10.36 8.26 7.14 36.98
14.33 3.92 1.73 7.51 5.64 13.11 13. 21.45 12.12 6.58 7.18 15.55
23.34 18.46 4.73 9.59 10.19 15.94 9.67 22.98 9.52 7.83 17.11 11.28
9.97 7.39 13.65 3.13 15.17 2.94 4.5 14.81 3.76 12.93 10.27 13.98
17.21 10.42 2.98 10.4 16.59 4.82 16.74 5.29 7.53 7.79 13.27 13.44
12.86 14.79 11.41 14.98 6.86 4.84 13. 13.45 23.09 20.31 20.32 15.7
25.41 9.93 6.73 21.08 12.6 6.68 19.88 7.44 16.44 4.98 7.43 3.26
12.03 3.57 5.89 6.93 12.01 6.92 3.73 3.11 10.59 12.87 6.65 18.13
11.32 8.79 8.93 30.81 5.49 34.77 19.92 18.06 4.85 6.36 28.32 26.42
6.75 7.56 17.6 12.26 18.71 6.48 5.91 6.12 3.81 9.62 14.27 18.06
22.11 17.15 16.42 30.63 8.2 6.72 7.44 13.61 11.48 3.56 3.95 24.39
6.87 5.12 23.24 17.27 5.81 16.47 30.62 16.29 6.58 17.44 10.13 20.85
8.43 15.02 18.85 15.39 3.33 12.8 5.68 2.96 3.32 13.28 12.5 3.11
13.04 27.71 17.19 13.15 18.68 19.31 7.6 23.29 30.59 13.99 29.53 8.23
29.68 6.29 6.19 8.51 18.13 19.69 8.01 8.61 5.19 13.22 15.76 27.38
10.45 5.52 5.68 16.51 9.81 10.56 23.97 9.64 13.35 4.32 5.03 9.28
19.37 5.5 14.36 6.72 8.44 4.7 11.22 4.16 23.98 17.1 12.67 2.97
3.59 11.74 2.87 10.3 18.8 14.69].
Reshape your data either using array.reshape(-1, 1) if your data has a single feature or array.reshape(1, -1) if it contains a single sample.`
riusciresti a spiegarmi, grazie mille
The text was updated successfully, but these errors were encountered: