1. A method for predicting one or more states of a subject, the method comprising: obtaining training data comprising a plurality of variables; obtaining one or more training states associated with the training data; and forming a predictive model according to the training data and the one or more training states, the predictive model predictive of the one or more training states, wherein the forming of the predictive model comprises extracting one or more hidden components from the training data, wherein the extracting of the one or more hidden components comprises regression analysis comprising determining one or more relationships between the one or more hidden components and the plurality of variables, and determining one or more relationships between the one or more hidden components and the one or more training states, and wherein a number of the one or more hidden components is less than a number of the plurality of variables and greater than a number of the one or more training states; and wherein one or more of the obtaining of the training data, the obtaining of the one or more training states, and the forming of the predictive model are implemented as instruction code executed on a processor device; wherein the extracting of the one or more hidden components further comprises: minimizing a regularized total loss comprising a regularized loss of a first matrix comprising the training data and a regularized loss of a second matrix comprising the one or more training states; and forming a third matrix, a fourth matrix and a fifth matrix; wherein most of the data in the third matrix equals zero; most of the data in the fourth matrix equals zero; most of the data in the fifth matrix equals zero; and wherein the minimizing of the regularized total loss comprises: calculating the third, the fourth and the fifth matrices by setting all data in the third, the fourth and the fifth matrices to known values; recalculating the fourth matrix, while the third and fifth matrices do not change, by substantially minimizing a regularized loss for the fourth matrix; recalculating the third matrix, while the fourth and fifth matrices do not change, by substantially minimizing a regularized loss for the third matrix; recalculating the fifth matrix, while the third and fourth matrices do not change, by substantially minimizing a regularized loss for the fifth matrix; and comparing the regularized total loss to a predetermined threshold and if the regularized total loss is above the predetermined threshold, repeating the calculating, recalculating and comparing steps.