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NEW QUESTION: 1
You create a binary classification model to predict whether a person has a disease.
You need to detect possible classification errors.
Which error type should you choose for each description? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:
Explanation:

Explanation:
Box 1: True Positive
A true positive is an outcome where the model correctly predicts the positive class Box 2: True Negative A true negative is an outcome where the model correctly predicts the negative class.
Box 3: False Positive
A false positive is an outcome where the model incorrectly predicts the positive class.
Box 4: False Negative
A false negative is an outcome where the model incorrectly predicts the negative class.
Note: Let's make the following definitions:
"Wolf" is a positive class.
"No wolf" is a negative class.
We can summarize our "wolf-prediction" model using a 2x2 confusion matrix that depicts all four possible outcomes:
Reference:
https://developers.google.com/machine-learning/crash-course/classification/true-false-positive-negative

NEW QUESTION: 2
The phase 0 of Risk Management Framework (RMF) is known as strategic risk assessment planning. Which of the following processes take place in phase 0?
Each correct answer represents a complete solution. Choose all that apply.
A. Establish criteria that will be used to evaluate threats, vulnerabilities, and controls.
B. Review documentation and technical data.
C. Establish criteria that will be used to classify and rank data assets.
D. Identify threats, vulnerabilities, and controls that will be evaluated.
E. Apply classification criteria to rank data assets and related IT resources.
Answer: A,C,D,E

NEW QUESTION: 3
When performing several inserts into a table defined with an identity column, which attribute could be ALTERed to help with the performance?
A. RESET
B. CACHE
C. MAXVALUE
D. INCREMENT
Answer: D