145 | | # The commands above use default values for the default values for the rank, k, of the NMF and the homogeneity parameter, lambda. |
146 | | # Generally, the rank should be chosen to be large enough to capture structure in the data matrix, yet small enough that the factorization |
147 | | # gives reproducible interpretations under multiple non-unique solutions. Increasing the homogeneity parameter places greater emphasis |
148 | | # on the common factors in the integration. The heuristic functions suggestK and suggestLambda can be used to guide the data-set-specific |
| 145 | # The commands above use default values for the rank, k, of the NMF and the homogeneity parameter, lambda. Generally, the rank |
| 146 | # should be chosen to be large enough to capture structure in the data matrix, yet small enough that the factorization gives reproducible |
| 147 | # interpretations under multiple non-unique solutions. Increasing the homogeneity parameter places greater emphasis on the common |
| 148 | # factors in the integration. The heuristic functions suggestK and suggestLambda can be used to guide the data-set-specific |