質問編集履歴
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コードとエラーを追記いたしました。
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@@ -14,23 +14,80 @@
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### 発生している問題・エラーメッセージ
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```
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ValueError Traceback (most recent call last)
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~\AppData\Local\Temp/ipykernel_19348/2698015120.py in <module>
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----> 1 housing_pcp.fit(X_train,y_train)
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~\anaconda3\lib\site-packages\sklearn\linear_model\_stochastic_gradient.py in fit(self, X, y, coef_init, intercept_init, sample_weight)
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727 Returns an instance of self.
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728 """
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--> 729 return self._fit(X, y, alpha=self.alpha, C=1.0,
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730 loss=self.loss, learning_rate=self.learning_rate,
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731 coef_init=coef_init, intercept_init=intercept_init,
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~\anaconda3\lib\site-packages\sklearn\linear_model\_stochastic_gradient.py in _fit(self, X, y, alpha, C, loss, learning_rate, coef_init, intercept_init, sample_weight)
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567 self.t_ = 1.0
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568
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--> 569 self._partial_fit(X, y, alpha, C, loss, learning_rate, self.max_iter,
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570 classes, sample_weight, coef_init, intercept_init)
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571
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~\anaconda3\lib\site-packages\sklearn\linear_model\_stochastic_gradient.py in _partial_fit(self, X, y, alpha, C, loss, learning_rate, max_iter, classes, sample_weight, coef_init, intercept_init)
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497 n_samples, n_features = X.shape
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498
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--> 499 _check_partial_fit_first_call(self, classes)
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500
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501 n_classes = self.classes_.shape[0]
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\anaconda3\lib\site-packages\sklearn\utils\multiclass.py in _check_partial_fit_first_call(clf, classes)
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~\anaconda3\lib\site-packages\sklearn\utils\multiclass.py in _check_partial_fit_first_call(clf, classes)
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337 else:
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338 # This is the first call to partial_fit
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--> 339 clf.classes_ = unique_labels(classes)
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340 return True
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341
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~\anaconda3\lib\site-packages\sklearn\utils\multiclass.py in unique_labels(*ys)
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96 _unique_labels = _FN_UNIQUE_LABELS.get(label_type, None)
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97 if not _unique_labels:
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---> 98 raise ValueError("Unknown label type: %s" % repr(ys))
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100 ys_labels = set(chain.from_iterable(_unique_labels(y) for y in ys))
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ValueError: Unknown label type: (array([ 5. , 6.3, 7. , 7.2, 8.1, 8.3, 8.5, 8.7, 8.8, 9.5, 9.6,
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10.2, 10.4, 10.5, 10.8, 10.9, 11.3, 11.5, 11.7, 11.8, 11.9, 12. ,
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12.1, 12.5, 12.6, 12.7, 12.8, 13. , 13.1, 13.2, 13.3, 13.4, 13.5,
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13.6, 13.8, 13.9, 14. , 14.1, 14.2, 14.3, 14.4, 14.5, 14.6, 14.8,
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14.9, 15. , 15.1, 15.2, 15.3, 15.4, 15.6, 15.7, 16. , 16.1, 16.2,
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16.3, 16.4, 16.6, 16.7, 16.8, 17.1, 17.3, 17.4, 17.5, 17.6, 17.7,
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17.8, 17.9, 18. , 18.1, 18.2, 18.3, 18.4, 18.5, 18.8, 18.9, 19. ,
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19.1, 19.2, 19.3, 19.4, 19.5, 19.6, 19.7, 19.8, 19.9, 20. , 20.1,
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20.2, 20.3, 20.4, 20.5, 20.6, 20.7, 20.8, 20.9, 21. , 21.1, 21.2,
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21.4, 21.5, 21.6, 21.7, 21.8, 21.9, 22. , 22.1, 22.2, 22.3, 22.4,
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22.5, 22.6, 22.7, 22.8, 22.9, 23.1, 23.2, 23.3, 23.4, 23.6, 23.7,
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23.8, 23.9, 24. , 24.1, 24.2, 24.3, 24.4, 24.5, 24.6, 24.7, 24.8,
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25. , 25.1, 25.2, 25.3, 26.4, 26.5, 26.6, 27. , 27.1, 27.5, 27.9,
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28. , 28.2, 28.4, 28.5, 28.6, 28.7, 29. , 29.1, 29.6, 29.8, 29.9,
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30.1, 30.3, 30.7, 30.8, 31. , 31.1, 31.5, 31.6, 31.7, 32. , 32.2,
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32.4, 32.5, 32.7, 33. , 33.1, 33.2, 33.4, 33.8, 34.6, 34.7, 34.9,
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35.1, 35.2, 35.4, 36. , 36.1, 36.2, 36.4, 36.5, 37. , 37.3, 37.6,
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37.9, 39.8, 41.7, 42.3, 43.1, 43.5, 43.8, 44. , 45.4, 46. , 46.7,
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48.5, 48.8, 50. ]),)
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```
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### 該当のソースコード
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```ここに言語名を入力
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from sklearn.preprocessing import StandardScaler
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sc = StandardScaler()
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sc.fit(housing_X)
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housing_X = sc.transform(housing_X)
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from sklearn.model_selection import train_test_split
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X_train, X_test, y_train, y_test = train_test_split(housing_X,housing_y, test_size = 0.3, random_state=0)
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from sklearn.linear_model import Perceptron
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# 学習
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housing_pcp = Perceptron(max_iter=40, tol=1e-3, eta0=1.0, shuffle=True)
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housing_pcp.fit(X_train,y_train)
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```
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