Charlie Brown sorry I’m late I had to walk my dog Snoopy shirt
Be considerate of others on your flight. You can recline, but don’t do it during food service. If you get up, put your seat up, don’t just leave it back. Don’t shout, wear headphones when doing anything that produces noise on an electronic device(I don’t care how quiet you think it is, we are close by and can hear it), be conscious of body odor, don’t wear perfume, cologne, or scented lotion. Get up if someone next to you needs to get out of the row. Don’t spread into another person’s seat. Read your fellow passengers in terms of if they want to converse with you. Niceties are fine, but most won’t want to speak for hours with you.
In Classification, you first 'learn' what goes with what and then you 'apply' that knowledge to new examples. So if somebody gave us the first picture on the left, which is a plot of hair length (Y axis) against gender (on X axis, however sorted such that the points belonging to females, corresponding to blue color, appear first, followed by male, corresponding to red color), the task of a classification model would be to learn the fact that typically females have longer hair than males and then use this knowledge and apply it to graph (obtained from different sets of people) shown on the right where there is no color coding done. A classifier then has to look at each black point, see its Y axis value and from the knowledge it acquired from left graph, guess if it should be blue or red.
In Classification, you first 'learn' what goes with what and then you 'apply' that knowledge to new examples. So if somebody gave us the first picture on the left, which is a plot of hair length (Y axis) against gender (on X axis, however sorted such that the points belonging to females, corresponding to blue color, appear first, followed by male, corresponding to red color), the task of a classification model would be to learn the fact that typically females have longer hair than males and then use this knowledge and apply it to graph (obtained from different sets of people) shown on the right where there is no color coding done. A classifier then has to look at each black point, see its Y axis value and from the knowledge it acquired from left graph, guess if it should be blue or red.
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