My company, General Dexterity, is a technology company that works with the creation of machines that can replace human labor in factories and make production faster, more efficient and more dynamic. To achieve these objectives, we have a team of programmers and engineers who have been working daily to develop software and hardware capable of leading our company to progress and we have achieved, our company has been successful and we have achieved good results in our projects.
However, something has worried me about our team of programmers. After many observations, I discovered that our programmers are being subjected to abusive working hours that are harmful to their health and productivity. Programmers are working on abusive hours, which promotes poor quality food and rest. At all times, I see them extremely tired and unmotivated, although they continue to do their jobs excellently. This has worried me, because if our programmers continue with these routines they will have health problems and our productivity will decrease.
After thinking about it, I decided that some changes should be made to improve the quality of our team. First, I decided that the team of programmers will be divided into sub-teams that will work on different shifts and on different projects, to promote rest. In addition, I stipulated that all programmers must have a schedule for meals. Nevertheless, the deadline for the completion of the projects will increase by three days.
I believe that the changes will be beneficial for the company and that the result will be very promising.
Noise is known as a kind of mislabeled or errors seen in the values of attribute but outlier is known to be wider concept that is also made up of not only errors but discordant data that occurs due to natural variation inside a population.
<h3>What is outlier in data mining?</h3>
An Outlier is known to be a kind of data object that moves from the rest of the data objects and can work in different way.
Note that outliers can be interesting or say desirable, but noise is not.
Noise data can be seen as normal data and as such, noise objects are not always outliers.
Note also that outliers would not be classify as noise objects. Note that the source of noise in data can be random and as such can be seen as unusual.
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Answer:
Put a comma after sharp. Put a comma after elongated.
Explanation:
