SparseTSF

Description

This API calls the SparseTSF model, which can be used for time series forecasting.

SparseTSF Model Architecture

Image Source: SparseTSF: Modeling Long-term Time Series Forecasting with 1k Parameters Shengsheng Lin et al

SparseTSF is lightweight model for Long-term Time Series Forecasting.

Learning Process:

  • Data Input

    • The model receives the time series data as input.
  • Down Sampling

    • The data is divided into smaller chunks based on predefined periods.
  • Cross-Period Sparse Forecasting

    • Predictions are made for each of the divided periods independently.
  • Up Sampling

    • The individual period predictions are merged to produce the final forecasting result.

Key Features of SparseTSF:

  • Cross-Period Sparse Forecasting
    • A method that downsamples the original time series data into regular periods to separate seasonality and trends.
    • This approach significantly reduces model complexity and the number of parameters.
    • It is an optimization technique specifically designed for long-term forecasting.

API module path

from api.v2.model.SparseTSF import SparseTSF

Parameters

enc_in

  • Specifies the input feature size.
  • Example
    • If data's shape (x,x,1).
    • enc_in = 1

seq_len

  • Specifies the length of the input sequence.
  • Example
    • If data's shape (x,10,x).
    • seq_len = 10

pred_len

  • Specifies the prediction length.
  • Example
    • pred_len = 1

period_len

  • Specifies the length of the sub-sequence.
  • This value cannot exceed the seq_len.
  • Example
    • period_len = 1

d_model

  • Specifies the hidden dim size.
  • This value sets the number of nodes in the intermediate layer.
  • Example
    • This value is typically set as a power of 2.
    • d_model = 128

model_type

  • Specifies the forecasting model.
  • Option
    • 'linear'
    • 'mlp'
      • consist of Linear layer
  • Example
    • model_type = 'mlp'

Use_revin

  • Specifies whether to use RevIN normalization.
  • default : False
  • Example
    • Use_revin = False

Example Sample Code (Python)

Results

Check the entire module code.

datahub/api/v2/model/SparseTSF.py at main · machbase/datahub
All Industrial IoT DataHub with data visualization and AI source - machbase/datahub

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