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NEW QUESTION: 1
You have a model with a large difference between the training and validation error values.
You must create a new model and perform cross-validation.
You need to identify a parameter set for the new model using Azure Machine Learning Studio.
Which module you should use for each step? To answer, drag the appropriate modules to the correct steps. Each module may be used once or more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Box 1: Split data
Box 2: Partition and Sample
Box 3: Two-Class Boosted Decision Tree
Box 4: Tune Model Hyperparameters
Integrated train and tune: You configure a set of parameters to use, and then let the module iterate over multiple combinations, measuring accuracy until it finds a "best" model. With most learner modules, you can choose which parameters should be changed during the training process, and which should remain fixed.
We recommend that you use Cross-Validate Model to establish the goodness of the model given the specified parameters. Use Tune Model Hyperparameters to identify the optimal parameters.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/partition-and-sample
NEW QUESTION: 2
Your cluster's HDFS block size in 64MB. You have directory containing 100 plain text files, each of which is 100MB in size. The InputFormat for your job is TextInputFormat. Determine how many Mappers will run?
A. 0
B. 1
C. 2
D. 3
Answer: B
Explanation:
Each file would be split into two as the block size (64 MB) is less than the file size
(100 MB), so 200 mappers would be running.
Note:
If you're not compressing the files then hadoop will process your large files (say 10G), with a
number of mappers related to the block size of the file.
Say your block size is 64M, then you will have ~160 mappers processing this 10G file (160*64 ~=
10G). Depending on how CPU intensive your mapper logic is, this might be an
acceptable blocks size, but if you find that your mappers are executing in sub minute times, then
you might want to increase the work done by each mapper (by increasing the block size to 128,
256, 512m - the actual size depends on how you intend to process the data).
Reference: http://stackoverflow.com/questions/11014493/hadoop-mapreduce-appropriate-input-
files-size (first answer, second paragraph)
NEW QUESTION: 3
Type a formula into cell F8 using the appropriate function to calculate the greatest value in the highlighted range. Press the Enter key when you have finished.
A. Option A
Type = max (F5:F7) -> press enter from the keyboard
Answer: A