Tabular Regressor

Upload a table of training samples

Output sample importances (optional)

Predict the values of:

columns rows

Try it with example data

Architecture options

Max weights:
Max neurons:
Max layers:
Max layer skip:

Sparse weights
Include bias
Allow I→O
connections

Instructions: This tool builds neural networks that predict outputs from inputs.

Upload a table^* of training samples containing both inputs and outputs. These examples will train the network. Specify the output rows or columns and click Submit.
The trained network opens in a new page, where you can a) predict the outputs of new samples, and b) export it as computer code for use in your own programs.

* Sample table must be a fully numeric, comma-separated .csv file with no empty fields. Max allowed: 100 kB file size, 1000 rows/columns, 1 header row/column. Generation time limited to 1 sec.