Welcome to DeepMTP’s documentation!

DeepMTP is a Python package implementing a flexible two-branch neural network architecture that makes it compatible with the majority of multi-target prediction problems.

Documentation

Release:

0.0.23.dev106+g7f93bcc81

Date:

Jul 29, 2026

Contents:

• Installation
  • Requirements
  • Install from PyPI
  • Optional integrations
  • Install from source
• Migrating from DeepMTP 0.0.22
  • Before upgrading
  • Python and dependencies
  • Imports
  • Configuration
  • Data preparation
  • Prediction and training lifecycle
  • Checkpoints
  • Optional integrations and offline runs
  • Verification checklist
• Loading a dataset
  • Loading a built-in dataset
  • Loading a custom dataset
• Configuration options
  • General configuration
  • Instance and target branch hyperparameters
• Multiclass classification
  • Label contract
  • Model configuration
  • Metric averaging
  • Prediction output
  • Compatibility and current limits
• Mixed tabular inputs
  • Input format
  • Configuration
  • Preprocessing and checkpoints
  • Precomputed embeddings
• Hyperparameter Optimization
  • Hyperband
  • Combining Hyperband with DeepMTP
• Demo notebooks
• Project policies
• API reference
  • DeepMTP package
• Credits

Indices and tables

• Index

• Module Index

• Search Page