How to use the trained model on unseen data

[gioxc88]

It's not clear to me how to use TICC after training on test data.

Say I have a dataset X with 100 samples and I want to train on the first 50 and test it on the remaining 50.
Could you elaborate on how to do that?

So basically when you have new points how are those assigned to the cluster?
From what I understand I need to calculate the LLE matrix of dimension n_samples x n _clusters and then run the updateClusters function which is the dynamic programming algorithm that, given the trained inverse covariances for each cluster, works out the optimal cluster assignment for each point.

My question is do I need to concatenate the trained LLE with the new LLE deriving from the test data points?
Because the results will change depending on if I do that or not.

Many thanks
Gio

[ren-1247]

It's not clear to me how to use TICC after training on test data.

Say I have a dataset X with 100 samples and I want to train on the first 50 and test it on the remaining 50.
Could you elaborate on how to do that?

So basically when you have new points how are those assigned to the cluster?
From what I understand I need to calculate the LLE matrix of dimension n_samples x n _clusters and then run the updateClusters function which is the dynamic programming algorithm that, given the trained inverse covariances for each cluster, works out the optimal cluster assignment for each point.

My question is do I need to concatenate the trained LLE with the new LLE deriving from the test data points?
Because the results will change depending on if I do that or not.

Many thanks
Gio

Hi, do you know how to solve it? I would also like to ask the question of the test, the original is to use the real label to calculate its F1 score. After getting the trained inverse covariance, how to judge which class the new sample belongs to

[ykchasingwind]

I have the same issue