ZhiningLiu1998/TimeFuse
[ICML'25] Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting | 样本级别的自适应多模型集成时间序列预测
This tool helps people who need to forecast future trends from time series data, like sales figures, stock prices, or sensor readings. It takes in your historical time series data and uses a clever combination of different forecasting methods to produce more accurate future predictions. Anyone who relies on accurate time series forecasts for planning or decision-making would find this useful.
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Use this if you need highly accurate time series forecasts and want to leverage the strengths of multiple prediction models without manually choosing or combining them.
Not ideal if you only need simple, quick forecasts from a single model, or if you prefer to have full manual control over each individual forecasting model's configuration.
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25
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3
Language
Python
License
MIT
Category
Last pushed
May 22, 2025
Commits (30d)
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