FEDOT vs JADBio

FEDOT is a free, open-source framework for automating the creation of data-driven composite models. It supports classification, regression, clustering and time-series forecasting, with tabular, text and image inputs, including multimodal combinations. Its workflow covers preprocessing, model selection, tuning, cross-validation and serialization. Users can leave parameters unspecified for fuller automation or provide them to guide pipeline composition. FEDOT uses the GOLEM library to optimize graph-based pipelines with meta-heuristic methods. Presets include best_quality, fast_train, stable, auto, gpu, ts and automl; auto is the default. Data can come from CSV files, pandas DataFrames, NumPy arrays or time-series CSV data. It can be installed with pip, and the API can be called from a console without Python code, saving predictions as CSV files. GPU evaluation uses RAPIDS and supports a specified set of models. The project is distributed under the BSD 3-Clause license and supports Windows, Linux and macOS.

JADBio is a no-code automated machine learning platform for life scientists analyzing public or study data. It accepts curated CSV and other delimited files, and users choose the outcome to predict. Supported data includes genomics, transcriptome, metagenome, proteome, metabolome, clinical data, and images. Analysis features include automated preprocessing, feature selection, survival analysis, predictive modeling, and model interpretation; outputs can include predictive models, biomarkers or biosignatures, visualizations, and information for applying models. The REST API can add AutoML, including image analysis, to applications and automate workflows, with a Python client available through GitHub, PyPI, and Anaconda. JADBio offers web, API, and self-hosted options. Basic is free and includes one seat, three projects, a 50 MB upload limit, 500 MB storage, and one model export. Team is listed at $2,199 a year, billed annually, and includes a 14-day free trial. Business Pro has custom pricing and lists SaaS, AWS container, and on-premise delivery.