Dataset format: Text metric learning

Formats

The data for a text metric learning experiment can be formatted following format 1 or 2.

Format 1

A CSV file.

csv_name.csv (1)(2)

Format 2

A zip file containing a CSV file.

folder_name.zip (1)
│   └───csv_name.csv (2)

Note

You can have multiple CSV files in the zip file that you can use as train, validation, and test dataframes:

• A train CSV file needs to follow the format described above
• A validation CSV file needs to follow the same format as a train CSV file
• A test CSV file needs to follow the same format as a train CSV file, but does not require a label column

1. The available dataset connectors require the data for a text metric learning experiment to be in a zip or CSV file.
   Note

   To learn how to upload your zip or CSV file as your dataset in H2O Hydrogen Torch, see Dataset connectors.

2. A CSV file containing the following columns:
   • A text column containing the input texts
   • A label column containing the class names
     Note

     Texts that are similar should have the same class name.

   • An optional fold column containing cross-validation fold indexes
     Note

     The fold column can include integers (0, 1, 2, … , N-1 values or 1, 2, 3… , N values) or categorical values.

Example

The ubuntu_text_metric_learning.zip file is a preprocessed dataset in H2O Hydrogen Torch and was formatted to solve a text metric learning problem. The structure of the zip file is as follows:

ubuntu_text_metric_learning.zip
│   └───train.csv
│   └───test.csv

As follows, a random row from the train.csv file:

text	label	fold
what is the easiest way to strip a desktop edition to a server edition ?	16	1

Note

To learn how to access one of the preprocessed datasets in H2O Hydrogen Torch, see Demo (preprocessed) datasets.

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