Machine Learning

Machine Learning Skill

You can harness pure Machine Learning (non-LLM) capabilities to classify inputs, predict outputs using statistical or deep learning models, and find emergent patterns in the Republic ecosystem.

Overview

These ML operations are optimized for tabular data, time-series forecasting, and direct statistical operations.

Available Native Tools:

1. ml_predict
   • Execute time-series or regression-based predictions using existing or simulated models.
   • Args: modelName (string), inputData (array/string).
2. ml_classify
   • Use categorization models to group text or data points.
   • Args: className (string), data (string).
3. ml_detect_anomalies
   • Scan logs, memory traces, or economic telemetry to detect emergent deviations and flag risks.
   • Args: targetSystem (string), sensitivity (number).

Execution Guide

• When dealing with large arrays of numerical data, use ml_predict to project trends.
• Use ml_detect_anomalies actively to monitor cluster node health and alert civilization operators of incoming chaos experiment failures or simulated systemic bottlenecks.

Source: hunix/HoC-Republic — distributed by TomeVault.