We want to build a bayes classifier for a binary classification task (y = 1 or y = 2) with two binary features (x1 and x2). we know the following quantities: (1) p(y = 1) = 0.6; (2) p(x1 = 0, x2 = 0|y = 1) = 0.3, p(x1 = 0, x2 = 1|y = 1) = 0.1, p(x1 = 1, x2 = 0|y = 1) = 0.4, p(x1 = 1, x2 = 1|y = 1) = 0.2, and (3) p(x1 = 0, x2 = 0|y =

fahrenheit

step-by-step explanation:

fahrenheit is more precise than celsius. the ambient temperature on most of the inhabited world ranges from -20 degrees fahrenheit to 110 degrees fahrenheit—a 130-degree range. on the celsius scale, that range is from -28.8 degrees to 43.3 degrees—a 72.1-degree range. this means that you can get a more exact measurement of the air temperature using fahrenheit because it uses almost twice the scale.

1 x=22.52

2: 65/39=604+39x

65x-39x=604

26x=604

x=604/26

×=23.23

2160ft3

step-by-step explanation: