Answer:
A game is built from a combination of sub-tasks in order to provide the best experience to the user and make sure that the interface is comprises of only the results of the ongoing sub-tasks to provide a higher degree of data abstraction.
Data abstraction refers to the process of representing the essential information without including the background details. Rolling a dice is preferred to be a sub-task so that the user only gets to know about the result of the roll and does not have to wait for or anticipate the result. Moreover, a game may consist of n number of sub-tasks so it is not a good idea to include them in the main framework and are preferred to be abstracted.
Answer:
The answer is "Not all electronic health records can generate quality reports"
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Explanation:
The main objective of QI is to improve results, that uses the CDC to identifies improvement as just an aspect of the three-pronged service delivery scheme. It uses information for decision-making to improve strategies, initiatives, and outcomes, and other option can be described as follows:
- It the technology, which is fast enough.
- In this technology vendors are interested.
- In this, all the program does not require wireless networks.
Each person has a electronic chip-enabled ID card, which lets them vote on the internet. The ID card is put into the card reader that is connected the computer. :)
Answer:
Most Americans admire the life and work of Martin Luther King Jr., but their perception of him is smoke and mirrors.
Explanation:
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Answer:
The answer is nearest-neighbor learning.
because nearest neighbor learning is classification algorithm.
It is used to identify the sample points that are separated into different classes and to predict that the new sample point belongs to which class.
it classify the new sample point based on the distance.
for example if there are two sample points say square and circle and we assume some center point initially for square and circle and all the other points are added to the either square or circle cluster based on the distance between sample point and center point.
while the goal of decision tree is to predict the value of the target variable by learning some rules that are inferred from the features.
In decision tree training data set is given and we need to predict output of the target variable.
Explanation:
