Answer:
what table??
Step-by-step explanation:
For this case we must take into account the following conversions:
1 pound = 450 grams
1 mL = 0.00026 gallons
We apply the transformation of units to the following expression:
We have then:
Answer:
Applying both transformations to the given expression we have:
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.
A decagon has 10 sides.
It it is regular you can build 10 isosceles triangles from the center of the decagon to the 10 sides.
Each triangle has a common vertex where the angle of each triangle is 360° / 10 = 36°.
So each time that you rotate the decagon a multiple of 36° around the center you get an image that coincides with the original decagon.
If the letters are given clockwise:
- when you rotate 36° counter clockwise, the point A' (the image of A) will coincide with the point J.
- when you rotate 72° (2 times 36°) counter clockwise, the point A' will land on I.
- when you rotate 108° (3 times 36°) counter clockwise, the point A' will land on H.
- when you rotate 144° (4 times 36°) counter clockwise, the point A' will land on G.
- when you rotate 180° (5 times 36°) counter clockwise, the point A' will land on I.
- when you rotate 216° (6 times 36°) counter clockwise, the point A' will land on E.
- whn you rotate 252° (7 times 36°) counterclockwise, the point A' will coincide with D.
Add other 36° each time and A' will coincide successively with C, B and the same A.
<span>Using the formula above, your merit increase will be 2.5%. You received a score of 3.4 on your annual review. Since the merit increase model is 0.5% salary increase at a score of 2.6, with an additional 1% for every .4 points above that baseline, you get 2.5%, which is the baseline of 0.5% + 2% for the 0.8 points you scored above that baseline.</span>
