L2normalized
L2normalized refers to the process of L2 normalization, a method of scaling a vector so that its L2 norm equals one. The L2 norm of a vector x = (x1, x2, ..., xn) is defined as ||x||2 = sqrt(sum_i xi^2). The L2 normalization of x is x_hat = x / ||x||2, provided ||x||2 is nonzero. In practice, a small epsilon may be added to the denominator to avoid division by zero.
The result of L2 normalization is a unit vector with length one. This makes the vector’s direction
In many applications, normalization is performed per vector, per row, or per feature depending on the data
L2 normalization differs from other normalization schemes such as L1 normalization (sum of absolute values equals
Example: the vector [3, 4] has ||x||2 = 5, so its L2-normalized form is [0.6, 0.8].