ValueError n_components=100 must be between 0 and minn_samples n_features=61 with svd_solver=full

This error occurs when you are trying to perform dimensionality reduction using Principal Component Analysis (PCA) with an invalid number of components specified.

The error message indicates that the value of n_components=100 is not valid because it is greater than the minimum of n_samples and n_features, which is 61 in this case. This means that you are trying to reduce the number of dimensions to a value that is larger than the number of samples or features in your dataset.

To solve this error, you can either reduce the value of n_components to a valid value (e.g. 61 or lower), or increase the number of samples or features in your dataset if possible. Alternatively, you can try using a different dimensionality reduction technique that does not have this restriction, such as t-SNE or UMAP.