ROBUST CLASSIFICATION BY PRE-CONDITIONED LASSO AND TRANSDUCTIVE DIFFUSION COMPONENT ANALYSIS

摘要

Techniques are disclosed for identifying and filtering outliers from a sample set of data prior to training a classifier on an object using the sample set. A data set including a plurality of samples used to train a classification model is retrieved. The samples in the data set have a feature dimensionality. A graph of the data set is built. Each node in the graph corresponds to a sample in the data set and edges connecting the nodes correspond to a measure of similarity between the nodes. The feature dimensionality of the sample data set is reduced based on a topology of the graph. One or more outliers in the data set are identified based on the reduced feature dimensionality.