Normalize -1 ~ 1
Yes, there are ways to normalize data to the range between -1 and 1. One common method is called Min-Max normalization. It works by transforming the data to a new range, such that the minimum value is mapped to -1 and the maximum value is mapped to 1. The formula for this normalization is:
x_norm = (x - x_min) / (x_max - x_min) * 2 - 1
Where x_norm is the normalized value, x is the original value, x_min is the minimum value in the data and x_max is the maximum value in the data.
Another method for normalizing data to the range between -1 and 1 is called Z-score normalization, also known as standard score normalization. This method normalizes the data by subtracting the mean and dividing by the standard deviation. The formula for this normalization is:
x_norm = (x - mean) / standard deviation
Where x_norm is the normalized value, x is the original value, mean is the mean of the data and standard deviation is the standard deviation of the data.
there are many ways about normalize skils for ml and dl. It is known to provide only normalization for 0 to 1.
I want to know that is some ways to normalize -1 between 1.