@saehrimnir/druidjs / ParametersStressMDS
Interface: ParametersStressMDS
Defined in: dimred/index.js:71
Properties
| Property | Type | Description | Defined in |
|---|---|---|---|
d? | number | the dimensionality of the projection. | dimred/index.js:72 |
eig_args? | Partial<EigenArgs> | Parameters for the eigendecomposition algorithm. | dimred/index.js:86 |
epsilon? | number | stop once the relative stress improvement falls below this. | dimred/index.js:77 |
init_DR? | "MDS" | "PCA" | "random" | starting configuration. "MDS" runs classical MDS on the same distances, which is what keeps the non-convex descent out of the poor local minima this objective is known for. "PCA" needs the original data, not a precomputed matrix. | dimred/index.js:81 |
iterations? | number | maximum number of gradient steps. | dimred/index.js:76 |
learning_rate? | number | initial step size. Dimensionless: the gradient is preconditioned by the weighted degree, so this needs no rescaling for the data or the weighting. Adapted by the line search, so it only sets where the search starts. | dimred/index.js:78 |
metric? | Metric | "precomputed" | the metric which defines the distance between two points. Pass graph shortest-path distances as "precomputed" for a graph layout. | dimred/index.js:73 |
seed? | number | the seed for the random number generator. | dimred/index.js:85 |
weights? | WeightSpec | Pair weighting, see WeightSpec. | dimred/index.js:75 |