Ross ROSS = Recommend OSS · open-source software intelligence for agents

reiinakano/xcessiv

A web-based application for quick, scalable, and automated hyperparameter tuning and stacked ensembling in Python. observed · 2026-08-28

github.com/reiinakano/xcessiv · homepage · Python · Apache-2.0 (permissive) observed · 2026-08-28

Health v2 · maintenance only

23/100

  • Activity 0
  • Release rhythm 8
  • Longevity 100
How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.

  • gap_med: n/a
  • age_days: 3466
  • days_rel: n/a
  • days_push: 3010
  • n_releases_24m: 0

Full methodology

Adoption not part of the score

1265 stars · 107 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Xcessiv is a web-based Python application for building, tuning, and managing stacked machine learning ensembles. It provides a GUI for defining base learners, running parallel hyperparameter searches, and exporting ensembles as standalone Python code.

Use cases

  • build stacked ensembles for kaggle competitions
  • automate hyperparameter tuning of scikit-learn models
  • compare hundreds of model-hyperparameter combinations
  • run parallel hyperparameter searches across multiple cores
  • export a stacked ensemble as a standalone python file
  • automate ensemble construction with greedy model selection

When to choose

  • you want a GUI-driven workflow for stacked ensembling with scikit-learn-compatible models
  • you need to track and compare many model-hyperparameter combinations in one place
  • you want automated hyperparameter search via Bayesian optimization and TPOT integration

When to avoid

  • you need actively maintained software - the last release was in 2018
  • you work outside the scikit-learn API ecosystem
  • you need deep learning or GPU-based model training workflows

Facets

application · maturity abandoned

machine-learning data-science gui machine-learning data-science python cross-platform stacked-ensembles hyperparameter-optimization automl scikit-learn bayesian-optimization tpot web-server

2 sources

Member repositories

RepositoryRoleHealth v2
reiinakano/xcessivmain23

For agents

markdown · JSON · MCP: product_card(name="reiinakano/xcessiv")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem