Uma biblioteca para realizar previsões em SVR com aprendizado online

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  • License: MIT License
  • Author: Ademir Neto
  • Requires: Python >=3.9
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Project description

My Library

Uma biblioteca para realizar experimentos com séries temporais utilizando SVR, Random Walk, e métricas de avaliação. Inclui suporte para pré-processamento de dados, criação de lags, e execução de testes como Diebold-Mariano e métricas específicas para séries temporais.

Recursos Principais

  • SVR Predict: Previsões offline utilizando Suporte a Vetores de Regressão.
  • Random Walk Predict: Implementação de Random Walk como baseline.
  • SVR Online: Aprendizagem incremental com atualização dinâmica do modelo.
  • Métricas: Cálculo de MSE, MAPE, U de Theil, WPOCID e testes estatísticos como Diebold-Mariano.

Instalação

Para instalar a biblioteca, execute:

pip install online-pso

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  • License: MIT License
  • Author: Ademir Neto
  • Requires: Python >=3.9
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1.0.0

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