Systems and methods for automatically identifying outliers in a machine learning training dataset

A system for automatically identifying at least one outlier in a training set corresponding to a label for a neural network, comprising:

• a data storage configured to store the training set;
• an embedding generator configured to generate an embedding vector for each element of the training set which is a numeric representation of that element;
• a centroid generator configured to compute a centroid of the elements equal to an average value for all the embedding vectors for all the elements from the training set;
• a dissimilarity score calculator configured to calculate, for all the elements in the training set, a dissimilarity score, wherein the dissimilarity score equals to a distance between the embedding vector of the element and the centroid;
• and
• an outlier selector configured to identify and to mark elements from the training set such that the corresponding embedding vectors of the elements have the dissimilarity score higher than or equal to a predetermined threshold value.