PALEmbeddings

class hana_ml.text.pal_embeddings.PALEmbeddings(model_version=None, max_token_num=None)

Embeds input documents into vectors.

Examples

Assume we have a hana dataframe df which has two columns: 'ID' and 'TEXT' and then we could invoke create a PALEmbeddings instance to embed the documents into vectors.

>>> embed = PALEmbeddings()
>>> vectors = embed.fit_transform(data=df, key='ID', target='TEXT')
>>> vectors.collect()
Attributes:
result_DataFrame

The embedding result.

stat_DataFrame

The statistics.

Methods

fit_transform(data, key, target[, ...])

Getting the embeddings.

fit_transform(data, key, target, thread_number=None, batch_size=None, is_query=None, max_token_num=None)

Getting the embeddings.

Returns:
DataFrames

The result.

Inherited Methods from PALBase

Besides those methods mentioned above, the PALEmbeddings class also inherits methods from PALBase class, please refer to PAL Base for more details.