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NEW QUESTION: 1
How can content types be used in CRM Content? (Choose two answers.)
A. With library rules, to limit the number of libraries created.
B. With validation rules, to capture complete data.
C. With upload rules, to limit the size of content files.
D. With content fields, to control the content detail page layout.
Answer: B,D
NEW QUESTION: 2
あなたはMicrosoft SQL Server2012環境を管理します。SQL Server 2012のインスタンスのいずれかがSalesという名前のデータベースが含まれています。
あなたはWindows Azure SQLデータベースへの販売に移行する予定です。
そのためには、含まれているデータベースを実装する必要があります。
あなたは何をすべきか。(それぞれの正しい答えはソリューションの一部を提供します。該当することをすべて選択してください。)
A. FULLにデータベースコンテインメントを設定します。
B. 分的にデータベースコンテインメントを設定します。
C. サーバープロパティContained Database Authenticationを無効にします。
D. EサーバープロパティContained Database Authenticationを有効にします。
E. サーバープロパティクロスdbオーナーシップチェイニングを無効にします。
F. Azureにデータベースコンテインメントを設定します。
Answer: B,D
NEW QUESTION: 3
You are evaluating a Python NumPy array that contains six data points defined as follows:
data = [10, 20, 30, 40, 50, 60]
You must generate the following output by using the k-fold algorithm implantation in the Python Scikit-learn machine learning library:
train: [10 40 50 60], test: [20 30]
train: [20 30 40 60], test: [10 50]
train: [10 20 30 50], test: [40 60]
You need to implement a cross-validation to generate the output.
How should you complete the code segment? To answer, select the appropriate code segment in the dialog box in the answer area.
NOTE: Each correct selection is worth one point.
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: 4
エンドツーエンドのパフォーマンスメトリクスを表示し、分散アプリケーションのトラブルシューティングを行う機能を提供するAWSサービスはどれですか？
A. AWS CodeStar
B. AWSX-Ray
C. AWSCIoud9
D. AWSクラウドマップ
Answer: B