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NEW QUESTION: 1
Ein Business Continuity Plan / Disaster Recovery Plan (BCP / DRP) bietet Folgendes:
A. Garantierte Wiederherstellung aller Geschäftsfunktionen
B. Versicherung gegen Rechtsstreitigkeiten nach einer Katastrophe
C. Schutz vor Verlust von Organisationsressourcen
D. Minimierung der Entscheidungsfindung während einer Krise
Answer: C
NEW QUESTION: 2
次のように定義された6つのデータポイントを含むPython NumPy配列を評価しています。
データ= [10、20、30、40、50、60]
Python Scikit-learn機械学習ライブラリのk-foldアルゴリズムの埋め込みを使用して、次の出力を生成する必要があります。
train: [10 40 50 60], test: [20 30]
train: [20 30 40 60], test: [10 50]
train: [10 20 30 50], test: [40 60]
出力を生成するには、相互検証を実装する必要があります。
どのようにコードセグメントを完成させるべきですか?回答するには、回答領域のダイアログボックスで適切なコードセグメントを選択します。
注:それぞれの正しい選択には1ポイントの価値があります。
Answer:
Explanation:
Explanation:
Box 1: k-fold
Box 2: 3
K-Folds cross-validator provides train/test indices to split data in train/test sets. Split dataset into k consecutive folds (without shuffling by default).
The parameter n_splits ( int, default=3) is the number of folds. Must be at least 2.
Box 3: data
Example: Example:
>>>
>>> from sklearn.model_selection import KFold
>>> X = np.array([[1, 2], [3, 4], [1, 2], [3, 4]])
>>> y = np.array([1, 2, 3, 4])
>>> kf = KFold(n_splits=2)
>>> kf.get_n_splits(X)
2
>>> print(kf)
KFold(n_splits=2, random_state=None, shuffle=False)
>>> for train_index, test_index in kf.split(X):
... print("TRAIN:", train_index, "TEST:", test_index)
... X_train, X_test = X[train_index], X[test_index]
... y_train, y_test = y[train_index], y[test_index]
TRAIN: [2 3] TEST: [0 1]
TRAIN: [0 1] TEST: [2 3]
References:
https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.KFold.html
NEW QUESTION: 3
A. Option D
B. Option A
C. Option C
D. Option B
Answer: B
NEW QUESTION: 4
Which logical storage relationship is correct?
A. Tablespace< Extent < Segment < Oracle Datablock
B. Data File <Tablespace< Segment < Extent < Oracle Datablock
C. Segment < Extent < Oracle Datablock<Tablespace
D. Tablespace< Segment < Extent < Oracle Datablock
Answer: D
Explanation:
Explanation/Reference:
References:
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