4 ms·
The wording is a bit weird, but "squishing" here just means using a constant number (the normalization constant) and multiplying all numbers in a vector by it.
by sigmoid10 4y ago
The wording is a bit weird, but "squishing" here just means using a constant number (the normalization constant) and multiplying all numbers in a vector by it. E.g: Multiplying [0,2,2,0] by 2 gives you [0,4,4,0], which is better distributed over the I3 distribution [0,2,4] (which goes all the way to 4). Any additional values that might get lost to rounding between 0 and 2 could be more easily restored that way. E.g. [0,1,2,2,0] would become [0,2,2,2,0] without squishing and [0,2,4,4,0] with it.
- michaelbarton 4y agoAh thanks so the explanation, the second part is still a bit confusing for me. When the author writes "A normalization constant squishes the input distribution, for example, I5, into the target distribution, for example, I3." It makes me think normalisation in the range (0-2) which I3 is in. Do I have that right?