[amp_mcq option1=”large enough to yield meaningful results” option2=”is representative of the dataset as a whole” option3=”both A and B” option4=”none of the above” correct=”option3″]<\/p>\n
The correct answer is C. both A and B.<\/p>\n
A good test dataset should be large enough to yield meaningful results, and it should be representative of the dataset as a whole. This means that the test dataset should be large enough to provide a statistically significant sample of the data, and it should include a variety of data points that are representative of the different types of data that are in the dataset.<\/p>\n
If the test dataset is too small, it may not be representative of the dataset as a whole, and the results of the test may not be accurate. If the test dataset is too large, it may be time-consuming and expensive to test, and the results may not be significantly different from the results of a smaller test dataset.<\/p>\n
It is important to note that a good test dataset is not necessarily a perfect dataset. There will always be some variation in the data, and there will always be some data points that are not representative of the dataset as a whole. However, a good test dataset should be large enough and representative enough to provide accurate results.<\/p>\n
Here are some additional details about each option:<\/p>\n
[amp_mcq option1=”large enough to yield meaningful results” option2=”is representative of the dataset as a whole” option3=”both A and B” option4=”none of the above” correct=”option3″]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[729],"tags":[],"class_list":["post-49179","post","type-post","status-publish","format-standard","hentry","category-machine-learning","no-featured-image-padding"],"yoast_head":"\n