🪐 Astrophage

Two-Stage Random Forest Classifier Model for NASA Kepler Object of Interest (KOI) Exoplanet Validation

What is Astrophage?

Astrophage is a high-performance exoplanet classification system built in Rust using Polars and a custom Two-Stage Random Forest implementation. It classifies Kepler Objects of Interest (KOIs) into three categories:

Class	Description	Count
CONFIRMED ✅	Validated exoplanets with high confidence	2,747
CANDIDATE 🔍	Promising signals awaiting follow-up confirmation	1,978
FALSE POSITIVE ❌	Non-planetary signals (stellar binaries, instrumental noise, etc.)	4,839

pie title Class Distribution in KOI Dataset
    "FALSE POSITIVE" : 4839
    "CONFIRMED" : 2747
    "CANDIDATE" : 1978

Total Samples: 9,564 | Features: 36 (28 base + 8 derived) | Accuracy: 94.81%

Why Two-Stage?

Our architecture mirrors NASA’s actual vetting workflow. Instead of forcing a single model to learn three classes simultaneously, we decompose the problem into two simpler binary decisions:

graph TD
    A[Raw KOI Data<br/>36 Features] --> B[Stage 1: CONFIRMED vs NOT CONFIRMED]
    B -->|CONFIRMED| C[Output: CONFIRMED ✅]
    B -->|NOT CONFIRMED| D[Stage 2: CANDIDATE vs FALSE POSITIVE]
    D -->|CANDIDATE| E[Output: CANDIDATE 🔍]
    D -->|FALSE POSITIVE| F[Output: FALSE POSITIVE ❌]

    style C fill:#2ecc71,stroke:#27ae60,color:#fff
    style E fill:#3498db,stroke:#2980b9,color:#fff
    style F fill:#e74c3c,stroke:#c0392c,color:#fff

This decomposition improves accuracy by ~3-4% over a single-stage classifier because each stage learns a simpler, cleaner decision boundary.

Key Results

Metric	Score
Accuracy	94.81%
Macro F1	92.64%
Weighted F1	94.51%

graph LR
    subgraph "Overall Metrics"
        A[Accuracy<br/>94.81%]
        B[Macro F1<br/>92.64%]
        C[Weighted F1<br/>94.51%]
    end

    style A fill:#2ecc71,stroke:#27ae60,color:#fff
    style B fill:#3498db,stroke:#2980b9,color:#fff
    style C fill:#9b59b6,stroke:#8e44ad,color:#fff

Quick Start

# Clone
git clone https://github.com/harihar-nautiyal/astrophage.git
cd astrophage

# Build
cargo build --release

# Run
./target/release/astrophage

Or try it in your browser with Google Colab — no installation needed!

Project Structure

graph TD
    A[astrophage/] --> B[Cargo.toml]
    A --> C[data/]
    A --> D[src/]
    A --> E[output/]

    C --> C1[koi_dataset.csv]

    D --> D1[main.rs]
    D --> D2[data.rs]
    D --> D3[features.rs]
    D --> D4[decision_tree.rs]
    D --> D5[model.rs]
    D --> D6[two_stage_model.rs]
    D --> D7[evaluation.rs]
    D --> D8[report.rs]

    E --> E1[report.json]

    style D1 fill:#f39c12,stroke:#e67e22,color:#fff
    style D6 fill:#2ecc71,stroke:#27ae60,color:#fff

Technology Stack

graph LR
    A[Astrophage] --> B[Rust]
    A --> C[Polars]
    A --> D[NDArray]
    A --> E[Tokio]
    A --> F[Serde]

    B --> B1[Memory Safety]
    B --> B2[Zero-Cost Abstractions]
    B --> B3[SIMD-Friendly]

    C --> C1[Fast CSV I/O]
    C --> C2[Columnar Operations]

    D --> D1[Vectorized Math]
    D --> D2[N-Dimensional Arrays]

    E --> E1[Async Runtime]

    F --> F1[JSON Serialization]

"Somewhere, something incredible is waiting to be known."
— Carl Sagan

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