Before revision:  In this paper, we propose a new feature selection method which uses singular value decomposition of a matrix and }]  the method of least squares to remove the irrelevant features and detect correlations between the remaining features . and remove those features whose weights are smaller than the threshold.
After revision:  In this paper, we propose a new feature selection method which uses singular value decomposition of a matrix and }] the corresponding column (feature). We define a threshold based on the local maxima of \mathbf{x and remove those features whose weights are smaller than the threshold.