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NEW QUESTION: 1
Which program will create a comma delimited raw data file (CSV)?
Answer:
Explanation:
Pending

NEW QUESTION: 2
A web browser need NOT always perform a complete request for a particular page that it suspects might NOT have changed. The HTTP specification provides a mechanism for the browser to retrieve only a partial response from the web server; this response includes information, such as the Last-Modified date but NOT the body of the page.
Which HTTP method will the browser use to retrieve such a partial response?
A. SEND
B. OPTIONS
C. ASK
D. HEAD
E. GET
F. TRACE
Answer: D

NEW QUESTION: 3
What are three features of the IPv6 protocol? (Choose three.)
A. optional IPsec
B. plug-and-play
C. checksums
D. autoconfiguration
E. complicated header
F. no broadcasts
Answer: B,D,F
Explanation:
Explanation/Reference:
Explanation:

NEW QUESTION: 4
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