PulseAugur / Brief
EN
LIVE 05:12:42

Brief

last 24h
[1/1] 221 sources

Multi-source AI news clustered, deduplicated, and scored 0–100 across authority, cluster strength, headline signal, and time decay.

  1. LLM Driven AutoForecasting with Sktime’s `craft()`

    A new approach integrates Large Language Models (LLMs) with the sktime library to automate time series forecasting pipeline selection. This method, dubbed `LLMBlueprintForecaster`, uses an LLM to generate Python constructor strings for sktime estimators. The `craft()` function within sktime then interprets these strings to build and evaluate forecasting pipelines iteratively, aiming to find the optimal model without extensive manual tuning. AI

    LLM Driven AutoForecasting with Sktime’s `craft()`

    IMPACT This method could streamline the process of building accurate time series forecasting models by leveraging LLMs to automate pipeline selection.