autoencoder

polars_ts.clustering._autoencoder

Autoencoder and clustering layer for deep embedded clustering.

TSAutoencoder

Bases: Module

              flowchart TD
              polars_ts.clustering._autoencoder.TSAutoencoder[TSAutoencoder]

              

              click polars_ts.clustering._autoencoder.TSAutoencoder href "" "polars_ts.clustering._autoencoder.TSAutoencoder"
            

1D convolutional autoencoder for time series.

Parameters

seq_len Length of (padded) input sequences. embedding_dim Dimension of the bottleneck embedding. n_filters Base number of convolutional filters.

encode(x)

Return bottleneck embedding.

decode(z)

Reconstruct from embedding.

forward(x)

Return (embedding, reconstruction).

ClusteringLayer

Bases: Module

              flowchart TD
              polars_ts.clustering._autoencoder.ClusteringLayer[ClusteringLayer]

              

              click polars_ts.clustering._autoencoder.ClusteringLayer href "" "polars_ts.clustering._autoencoder.ClusteringLayer"
            

Soft assignment via Student's t-distribution (DEC).

Parameters

n_clusters Number of clusters. embedding_dim Dimension of input embeddings. alpha Degrees of freedom of the Student's t-distribution. Default 1.0.

forward(z)

Compute soft cluster assignments q_ij.

target_distribution(q)

Compute sharpened target distribution from soft assignments.

Squares and normalizes q to produce a sharper auxiliary target that emphasizes high-confidence assignments.