bern_exp_pca: Bernoulli PCA
In krisrs1128/expPCA: Exponential Family PCA

Description Usage Arguments Value References

Bernoulli PCA

1 2	bern_exp_pca(X, n_comp = 2, n_cycle = 30, n_iter = 30, eps = 1e-04, lambda = 0.1, mu0 = NULL)

`X`	The n x p binary matrix with samples along rows which we want to decompose using exponential family PCA.
`n_comp`	How many principal components should we return?
`n_cycle`	How many times should the iterative optimization pass through across each component?
`n_iter`	The maximum number of iterations to run the PCA.
`eps`	The convergence criterion. If the mean change in the scores is less than eps, we return.
`lambda`	The regularization parameter in the optimization.
`mu0`	The value to regularize towards.

A list containing the converged values of A and V.

Collins, Michael, Sanjoy Dasgupta, and Robert E. Schapire. "A generalization of principal components analysis to the exponential family." Advances in neural information processing systems. 2001.

krisrs1128/expPCA documentation built on May 20, 2019, 1:26 p.m.