A: indication
B: indicate
C: indicated
D: indicting
举一反三
- The agenda should_____ the order of items and an estimated amount of time for each item.（ ） A: indication B: indicate C: indicated D: indicting
- What should be done at the end of each item on the agenda? Summarize the___at the end of each item on the agenda.
- On completing the planned items on the agenda, the chairperson should close the meeting. Which item should NOT be included in the closing speech? </p></p>
- 3. What is true about the point-to-point comparison? A: We move back and forth between Item A and Item B at each point B: We should discuss items in the same order throughout the essay C: It presents all the information about Item A and then all that about Item B D: Shifting between Item A and Item B makes the comparison easy to follow
- 3. A meeting agenda is important because it _______. A: tells the time and place of the meeting B: helps to give direction to the discussions C: contains items of interest to all those present D: shows who should speak at each stage of the meeting
内容
- 0
What is true about the point-to-point comparison? A: We move back and forth between Item A and Item B at each point. B: We should discuss items in the same order throughout the essay. C: Shifting between Item A and Item B makes the comparison easy to follow. D: It fully discusses Item A at first and then turns to Item B. E: It presents all the information about Item A and then all that about Item B.
- 1
Match each numbered item with the most closely related lettered item.
- 2
Which statement best describes the task of “regression” in machine learning? A: To assign a category to each item. B: To find the distribution of inputs in some space. C: To group data objects. D: To order items according to some criterion. E: To predict a real value for each item. F: To simplify inputs by mapping them into a lower space.
- 3
We should make ______ of meeting more regularly. A: an appointment B: an agenda C: an item D: a point
- 4
Which statement best describes the task of “regression” in machine learning? A: To assign a category to each item. B: To find the distribution of inputs in some space. C: To group data objects. D: To order items according to some criterion. E: To predict a real value for each item. F: To simplify inputs by mapping them into a lower space. G: None of the above is correct