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NEW QUESTION: 1
A. Option D
B. Option E
C. Option B
D. Option C
E. Option A
Answer: A,D,E
NEW QUESTION: 2
When creating a new IBM Watson Visual Recognition classifier, what is the recommended minimum number of images that needs to be provided (for both the positive and negative example sets) in order to obtain the best results?
A. 150-200
B. 500-1000
C. 1000-2000
D. 15-30
Answer: D
Explanation:
Explanation/Reference:
Reference http://www.aei.tuke.sk/papers/2017/1/08_Bundzel
NEW QUESTION: 3
You need to build a sentiment analysis solution that will use input data from JSON documents and PDF documents. The JSON documents must be processed in batches and aggregated.
Which storage type should you use for each file type? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
References:
https://docs.microsoft.com/en-us/azure/architecture/data-guide/big-data/batch-processing
NEW QUESTION: 4
You need to configure the Permutation Feature Importance module for the model training requirements.
What should you do? To answer, select the appropriate options in the dialog box in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
Box 1: 500
For Random seed, type a value to use as seed for randomization. If you specify 0 (the default), a number is generated based on the system clock.
A seed value is optional, but you should provide a value if you want reproducibility across runs of the same experiment.
Here we must replicate the findings.
Box 2: Mean Absolute Error
Scenario: Given a trained model and a test dataset, you must compute the Permutation Feature Importance scores of feature variables. You need to set up the Permutation Feature Importance module to select the correct metric to investigate the model's accuracy and replicate the findings.
Regression. Choose one of the following: Precision, Recall, Mean Absolute Error , Root Mean Squared Error, Relative Absolute Error, Relative Squared Error, Coefficient of Determination References:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/permutation-feature-importan