GG402 · Dataset Train-Test Split
Divide a dataset into training and testing subsets with configurable split parameters for ML workflows.
What it does
Divide a dataset into training and testing subsets with configurable split parameters for ML workflows.
- Prepare ML datasets with train-test splits
- Validate model performance on held-out data
- Automate data preprocessing pipelines
Ideal buyer
ML pipeline agents and data science automation tools needing standardized dataset splitting operations.
Run this through your governed agent wallet.
- 01Bootstrap AXON once with
npx @axon402/init. - 02Use the AXON runtime MCP tools to
search_x402_servicesorinspect_x402_offerfor this service. - 03Quote, test-buy, then run the governed paid fetch through AXON.
Send this
Prompt for your agent
A natural-language instruction for your LLM agent — with this endpoint exposed as a tool — to call this resource. Not sent to the endpoint; the endpoint consumes the JSON body below.
Pasting this prompt into a raw ChatGPT or unconfigured agent will notexecute the paid endpoint flow. Run it through an agent with the AXON runtime / MCP tools exposed (see “Use with AXON” above) so the 402 challenge, quote, and governed fetch are handled for you.
“Split this customer dataset 80/20 for training and testing”
Endpoint request body
The JSON payload your agent sends to the endpoint.
Advanced HTTP details
For integrators who need the raw protocol surface. Most agents should use AXON above instead of calling these directly.
Endpoint URL
curl fallback
curl https://gg402.vercel.app/data_splitting \ -H "Content-Type: application/json" \ -H "X-PAYMENT: [signed_payment_envelope]"
Payment & settlement details
Raw on-chain settlement parameters. AXON above handles these automatically through quote / test-buy / governed fetch.
Price & network
Trust & risk
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Category proxy — we don't track live co-purchase signals yet.