Using R (Studio), Python (Spyder), and PCA resources this pack is the effort of detecting anomalous data apart from legitimate instances. The training set contains only a few examples of anomalous data, and sitting alongside a large set of legitimate data, we create a robust PCA method in order strengthen discerning factors against counterfeit data.
DaScient/Principal-Component-Analysis-PCA-for-Counterfeit-Detection
Using R (Studio), Python (Spyder), and PCA resources this pack is the effort of detecting anomalous data apart from legitimate instances. The training set contains only a few examples of anomalous data, and sitting alongside a large set of legitimate data, we create a robust PCA method in order strengthen discerning factors against counterfeit data.
R