normalizor.RdThis function normalizes a matrix of features using precomputed means and standard deviations.
The function automatically runs load_scaler to read the standard deviations and means of the features,
which are organized into a list object named scaler. These means and standard deviations are computed from
the 10,000,000 datasets data.datasets for training the Pre-Trained Deep Neural Network (DNN).
normalizor(features)A matrix of the same dimensions as features, where each feature has been normalized.
The function applies z-score normalization to each element in the features matrix. It uses
the scaler object, which is expected to contain precomputed means and standard deviations for each feature.
The normalized value for each element is computed as:
$$z = \frac{x - \mu}{\sigma}$$
where \(x\) is the original value, \(\mu\) is the mean, and \(\sigma\) is the standard deviation.