Analyse
Embed
Step | Fast | Description |
---|---|---|
embed_dataset | Reduce the dataset to an n-dimensional numeric vector embedding | |
embed_images | Embed images using pretrained DL models | |
embed_items | Trains an item2vec model on provided lists of items (or sentences of words, etc.) | |
embed_sessions | Trains an item2vec model on provided lists of items | |
embed_text | Parse and calculate a (word-averaged) embedding vector for each text | |
embed_text_with_model | Use language models to calulate an embedding for each text in provided column | |
embed_with_trees | Reduce the dataset to an n-dimensional numeric vector embedding using a Forest model’s tree indices | |
layout_dataset | Reduce the dataset to 2 dimensions that can be mapped to x/y node positions | |
vectorize_dataset | Create a vectorized (numeric) dataset, (optionally) of reduced dimensionality |
Was this page helpful?