Answer:
Explanation:
Let's do this in Python, we can first generate the random number from 1 to 100. Then compare that with the input number from the guesser.
from random import random
random_0_1 = random()
random_1_100 = 1 if round(100*random_0_1) < 1 else round(100*random_0_1)
for trial in range(3):
guess = input('Guess the number: ')
if guess == random_1_11:
print('You guessed correctly!')
break
else:
print(2 - trial + " remaining try")
Answer:
Ask about next steps and the best way to communicate.
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Explanation:
Use the function varimp() on the output of train() and save it to an object called imp object.
<h3>What is the classification that has More than Two Classes and the Caret Package</h3>
In the Classification that has More than Two Classes and the Caret Package section, one need to use the methods that can be able to adapt to higher forms or dimensions and through a lot of different machine learning algorithms.
Note that varImp is seen as a generic method for calculating variable .
Hence, Use the function varimp() on the output of train() and save it to an object called imp object.
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Answer:
ExChunking is a good strategy for completing large assignments because it makes the work
less boring.
more thorough.
less difficult.
more manageable.planation:
Explanation: less difficult (C)
