The answer is D. All of the above.
The computational complexity of K-NN increases as the size of the training data set increase and the algorithm gets significantly slower as the number of examples and independent variables increase.
Also, K-NN is a non-parametric machine learning algorithm and as such makes no assumption about the functional form of the problem at hand.
The algorithm works better with data of the same scale, hence normalizing the data prior to applying the algorithm is recommended.
If you had 4 boxes of cereal and each costs $2.40, the total cost would be $9.60 (2.40×4).
The total cost of the bananas and the cereal cost $10.11. To find how much the 3/4 of bananas cost, simply subtract $9.60 away from $10.11 (10.11-9.6), which gives you $0.51.
The question asks for 1 pound of bananas but you only have the cost of 3/4. So, divide your cost by 3 to give you the cost of 1/4. (0.51÷3), which gives you $0.17.
The last step is to multiply this answer by 4 because 4/4 will result in a whole, or in this case, one pound (0.17×4) and thus gives you the cost $0.68 for one pound of bananas.
(please correct me if I'm wrong, hope this helped c: )
Okay so probability is just percentage of a whole, right?
So you have 14 White Eggs + 15 Brown Eggs + 11 Lemons.
Add all those numbers together and you get your whole.
14 + 15 = 29 29+11 = 40
40 is your whole.
So because you want to know how likely it is to pick up an egg, you would follow these steps.
100/40 = 2.5 (For each part of the 40, it is worth 2.5 percent.)
2.5 x 29 = 72.5
Your probability of picking an egg out of the bask is 72.5 percent or 72.5 out of 100.
Here are a few rules with exponents that you need to know:
- Dividing exponents of the same base:
For this, divide:
<u>Your final answer is 
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If there are no notebooks purchased, then Eula may buy 5 binders. If no binders are bought, then Eula may buy 10 notebooks. If 7 notebooks are purchased, then one binder may be purchased; this will also cause Eula to have $2 extra (maybe for tax).
