16. The method of claim 13 , wherein the anomaly score is compared to a threshold level to determine whether the input dataset contains an anomaly.
13. A method for outputting data based on anomaly detection, comprising: receiving an input dataset; generating, using a hardware processor, n-grams of different sizes from the input dataset; counting, using the hardware processor, the number of distinct n-grams in the n-grams of different sizes that are not present in a binary anomaly detection model; computing, using the hardware processor, an anomaly score based upon the number of distinct n-grams and a total count of the n-grams in the input dataset; using the anomaly score to determine whether an input dataset contains an anomaly; and outputting, using the hardware processor, the input dataset based on whether the input dataset contains an anomaly.