Normalize input data matrix
Mean centers each column of an input data matrix so that it has a mean of zero. Scales the entire matrix so that the largest absolute of the centered matrix is equal to unity.
normalize_input(X)
X |
matrix; Input data matrix with rows as observations and columns as variables/dimensions. |
Normalization avoids numerical problems when the coordinates (and thus the distances between observations) are very large. Directly computing distances on this scale may lead to underflow when computing the probabilities in the t-SNE algorithm. Rescaling the input values mitigates these problems to some extent.
A numeric matrix of the same dimensions as X but centred by column and scaled to have a maximum deviation of 1.
Aaron Lun
iris_unique <- unique(iris) # Remove duplicates iris_matrix <- as.matrix(iris_unique[,1:4]) X <- normalize_input(iris_matrix) colMeans(X) range(X)
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