SynthPred.jl

SynthPred.jl is a Julia package for synthetic data analysis, advanced imputation (ARIMA, RNN), AutoML, and ensemble modeling.

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🚀 Features

• 🔍 Descriptive statistics and missing data reporting
• 🧼 Simple and advanced imputation:
  • Mean, median, mode
  • Forward/backward fill
  • Gaussian distribution sampling
  • Time series-based: ARIMA
  • Sequence learning-based: RNN (Flux.jl)
• 🤖 AutoML for classification (MLJ.jl-based)
• ⚖️ Blending top-performing models via ensembling
• 📊 Predictions on new data
• 📑 JSON/CSV imputation reports

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📦 Installation

using Pkg
Pkg.add(url="https://github.com/TyMill/SynthPred.jl")

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🧪 Quick Example

using SynthPred
using CSV, DataFrames

# Load training data
df = CSV.read("data/example.csv", DataFrame)

# Explore data
SynthPred.Exploration.describe_data(df)

# Impute missing values (e.g. RNN strategy)
df_clean, report = SynthPred.Imputer.impute_advanced(df, "rnn", threshold=0.1)
SynthPred.Imputer.save_imputation_report(report, "reports/imputation_report.json")

# Run AutoML pipeline
top_models, scores = SynthPred.AutoML.run_automl(df_clean, :target)
X = select(df_clean, Not(:target))
y = df_clean[:, :target]
ensemble = SynthPred.AutoML.blend_top_models(top_models, X, y)

# Predict on new data
Xnew = CSV.read("data/new_data.csv", DataFrame)
preds = SynthPred.AutoML.predict_ensemble(ensemble, Xnew)
println(preds)

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📚 Documentation

Full documentation is available at: https://your-username.github.io/SynthPred.jl

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🧪 Project Structure

SynthPred/
├── Project.toml
├── src/
│   ├── SynthPred.jl
│   ├── Exploration.jl
│   ├── Imputer.jl
│   └── AutoML.jl
├── data/
│   ├── example.csv
│   └── new_data.csv
├── reports/
│   └── imputation_report.json
├── docs/
│   └── src/index.md
├── test/
│   └── runtests.jl
└── main.jl

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📌 Roadmap

• Core modules: Exploration, Imputer, AutoML
• ARIMA and RNN-based imputations
• AutoML + model blending with MLJ.jl
• Imputation reports (CSV/JSON)
• Documentation (Documenter.jl + GitHub Pages)
• Exporting trained models (JLD2, BSON)
• Web GUI with Pluto.jl or Dash.jl
• Integration with JuliaHub and Zenodo DOI

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🤝 Contributing

Pull requests are welcome! For major changes, please open an issue first to discuss your proposal.

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📜 License

MIT License © 2025 Tymoteusz Miller

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📬 Contact

📧 [email protected]

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Built with ❤️ in Julia for real-world ML and scientific discovery.