質問編集履歴
2
要請に基づいて修正
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test
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@@ -6,8 +6,6 @@
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どうすればいいか皆目見当がつきません。
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どうかご助力お願いします。
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コード
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#########################
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```python
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import numpy as np
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import random #擬似乱数を生成するライブラリー
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@@ -26,14 +24,10 @@
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np.random.seed(0) #乱数のシードの設定
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-
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def main():
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path_train = glob.glob("*****/*.jpg")
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-
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df_val = pd.read_csv("******/train.csv", index_col=0)
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print(df_val)
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df = pd.DataFrame({})
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for item in path_train:
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@@ -49,15 +43,11 @@
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peace = pd.DataFrame(list_value, columns=["image", "data"])
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peace = peace.set_index("image")
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df = pd.concat([df, peace], axis=0)
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print(df)
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print(df)
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X_train, X_test, y_train, y_test = train_test_split(df, df_val, test_size=0.2, random_state=0)
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-
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N_dim = 100 # 100列に落とし込む
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-
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pca = PCA(n_components=N_dim, random_state=0)
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pca.fit(X_train)
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@@ -73,20 +63,54 @@
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エラーメッセージ
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###############################
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--------------------------------------------------------------------------
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---------------------------------------------------------------------------
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TypeError Traceback (most recent call last)
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TypeError: only size-1 arrays can be converted to Python scalars
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The above exception was the direct cause of the following exception:
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ValueError Traceback (most recent call last)
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-
<ipython-input-
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<ipython-input-17-8d81aa9fba70> in <module>
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58 if __name__ == "__main__":
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---> 9
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---> 59 main()
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5 frames
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<ipython-input-17-8d81aa9fba70> in main()
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50 pca = PCA(n_components=N_dim, random_state=0)
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---> 51 pca.fit(X_train)
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53 X_train_pca = pca.transform(X_train)
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/usr/local/lib/python3.7/dist-packages/sklearn/decomposition/_pca.py in fit(self, X, y)
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380 Returns the instance itself.
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381 """
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--> 382 self._fit(X)
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383 return self
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384
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/usr/local/lib/python3.7/dist-packages/sklearn/decomposition/_pca.py in _fit(self, X)
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429
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430 X = self._validate_data(
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--> 431 X, dtype=[np.float64, np.float32], ensure_2d=True, copy=self.copy
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432 )
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433
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/usr/local/lib/python3.7/dist-packages/sklearn/base.py in _validate_data(self, X, y, reset, validate_separately, **check_params)
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564 raise ValueError("Validation should be done on X, y or both.")
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565 elif not no_val_X and no_val_y:
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--> 566 X = check_array(X, **check_params)
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567 out = X
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568 elif no_val_X and not no_val_y:
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/usr/local/lib/python3.7/dist-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, estimator)
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744 array = array.astype(dtype, casting="unsafe", copy=False)
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745 else:
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--> 746 array = np.asarray(array, order=order, dtype=dtype)
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747 except ComplexWarning as complex_warning:
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748 raise ValueError(
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/usr/local/lib/python3.7/dist-packages/pandas/core/generic.py in __array__(self, dtype)
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1991
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1992 def __array__(self, dtype: NpDtype | None = None) -> np.ndarray:
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1
要請に基づいて修正
test
CHANGED
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File without changes
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test
CHANGED
|
@@ -8,6 +8,7 @@
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8
8
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9
9
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コード
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10
10
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#########################
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11
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+
```python
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11
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import numpy as np
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import random #擬似乱数を生成するライブラリー
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from PIL import Image, ImageOps #画像処理ライブラリー
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@@ -67,7 +68,7 @@
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if __name__ == "__main__":
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main()
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```
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エラーメッセージ
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