I want to basically transform additional points after performing an initial fitting, but with a fitted model I load instead of one I just generated.
I tried to use class-transformer but got several errors.
So I tried the "manual" method of using JSON.stringify() on a already fitted UMAP model, then
const new = new UMAP({
nComponents: 2,
minDist: 0.5,
scale: 1,
nNeighbors: 2,
distanceFn: dist.similarity.manhattan
});
Object.keys(loaded).map((x) => (n[x] = stringfiedUMAP[x]));
This new object does have an transform function as expected, but calling it with
n.transform([myNewVector])
gives the error
TypeError: initFromRandom is not a function
Any help or tips here would be appreciated! Ideally it would be nice to be able to load a prefitted UMAP and transform new data points, just like MacInnes' Python implementation.
Thanks in advance!
I want to basically transform additional points after performing an initial fitting, but with a fitted model I load instead of one I just generated.
I tried to use
class-transformerbut got several errors.So I tried the "manual" method of using
JSON.stringify()on a already fitted UMAP model, thenThis new object does have an
transformfunction as expected, but calling it withgives the error
Any help or tips here would be appreciated! Ideally it would be nice to be able to load a prefitted UMAP and transform new data points, just like MacInnes' Python implementation.
Thanks in advance!