Robust convex biclustering method, computer equipment and readable storage medium

Abstract

The invention discloses a robust convex biclustering method in the technical field, and the method comprises the following steps: 1) data representation and symbol paraphrasing: dividing pollution data into the sum of clean data and sparse abnormal values; 2) constructing a robust convex biclustering model, and adding a Lasso type regularization item in an objective function of the robust convex biclustering model; 3) calculating a weight, ensuring that all data points contribute in calculation by using the weight, and reducing the number of non-zero items in a regularization sum by using k-nearest neighbor to simplify calculation; the method comprises the following steps of (1) optimizing a target function according to a variable V1 and a variable V2, (2) optimizing the target function according to the variable V1 and the variable V2, (3) using an alternating direction multiplier method ADMM to optimize the model, and carrying out variable updating according to an ADMM rule, (5) continuously iterating until the target function is converged, and (6) calculating a final clustering result according to the variable V1 and the variable V2 after convergence, and the method can better adapt to a complex and changeable data environment, and provides a firmer and more reliable support for data analysis and decision making.

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