README.md

---
license: mit
configs:
- config_name: anomaly
  data_files:
  - split: train
    path: anomaly/train-*
- config_name: autocorrelation_long_dependency
  data_files:
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    path: autocorrelation_long_dependency/train-*
- config_name: complex_multivariate_struct0
  data_files:
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    path: complex_multivariate_struct0/train-*
- config_name: complex_multivariate_struct1
  data_files:
  - split: train
    path: complex_multivariate_struct1/train-*
- config_name: complex_multivariate_struct2
  data_files:
  - split: train
    path: complex_multivariate_struct2/train-*
- config_name: complex_multivariate_struct3
  data_files:
  - split: train
    path: complex_multivariate_struct3/train-*
- config_name: complex_multivariate_struct4
  data_files:
  - split: train
    path: complex_multivariate_struct4/train-*
- config_name: complex_multivariate_struct5
  data_files:
  - split: train
    path: complex_multivariate_struct5/train-*
- config_name: complex_multivariate_struct6
  data_files:
  - split: train
    path: complex_multivariate_struct6/train-*
- config_name: complex_univariate
  data_files:
  - split: train
    path: complex_univariate/train-*
- config_name: cross_variable_learning_struct0
  data_files:
  - split: train
    path: cross_variable_learning_struct0/train-*
- config_name: cross_variable_learning_struct1
  data_files:
  - split: train
    path: cross_variable_learning_struct1/train-*
- config_name: cross_variable_learning_struct2
  data_files:
  - split: train
    path: cross_variable_learning_struct2/train-*
- config_name: cross_variable_learning_struct3
  data_files:
  - split: train
    path: cross_variable_learning_struct3/train-*
- config_name: cross_variable_learning_struct4
  data_files:
  - split: train
    path: cross_variable_learning_struct4/train-*
- config_name: datasetlength
  data_files:
  - split: train
    path: datasetlength/train-*
- config_name: longdistance
  data_files:
  - split: train
    path: longdistance/train-*
- config_name: noise
  data_files:
  - split: train
    path: noise/train-*
- config_name: period
  data_files:
  - split: train
    path: period/train-*
- config_name: trend
  data_files:
  - split: train
    path: trend/train-*
task_categories:
- time-series-forecasting
dataset_info:
- config_name: anomaly
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    dtype: int64
  - name: Feature1
    dtype: float64
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    num_examples: 360000
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- config_name: autocorrelation_long_dependency
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  - name: Feature1
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- config_name: complex_multivariate_struct0
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  - name: Feature2
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- config_name: complex_multivariate_struct1
  features:
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    dtype: string
  - name: interest_rate
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  - name: inflation
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  - name: gdp_growth
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  - name: unemployment_rate
    dtype: float64
  - name: consumer_spending
    dtype: float64
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    num_examples: 5000
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- config_name: complex_multivariate_struct2
  features:
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  - name: temperature
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  - name: rainfall
    dtype: float64
  - name: ice_cream_sales
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  - name: umbrella_sales
    dtype: float64
  - name: beverage_sales
    dtype: float64
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    num_examples: 5000
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- config_name: complex_multivariate_struct3
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- config_name: complex_multivariate_struct4
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  - name: economic_growth
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  - name: employment_rate
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  - name: market_confidence
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  - name: negative_indicator
    dtype: float64
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    num_examples: 5000
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- config_name: complex_multivariate_struct5
  features:
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    dtype: string
  - name: ad_spend
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  - name: sales
    dtype: float64
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    num_examples: 5000
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- config_name: complex_multivariate_struct6
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  - name: supply
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  - name: demand
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  - name: price
    dtype: float64
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    num_examples: 5000
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- config_name: complex_univariate
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- config_name: cross_variable_learning_struct0
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  - name: FeatureA_WhiteNoise
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  - name: FeatureB_Lag48
    dtype: float64
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    num_examples: 5000
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- config_name: cross_variable_learning_struct1
  features:
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  - name: FeatureB_Lag10
    dtype: float64
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    num_examples: 5000
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- config_name: cross_variable_learning_struct2
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  - name: FeatureA_Sin
    dtype: float64
  - name: FeatureB_Noise_0dB
    dtype: float64
  - name: FeatureC_Sum
    dtype: float64
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    num_examples: 5000
  download_size: 150800
  dataset_size: 160000
- config_name: cross_variable_learning_struct3
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  - name: FeatureA_WhiteNoise
    dtype: float64
  - name: FeatureB_Lag5
    dtype: float64
  splits:
  - name: train
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    num_examples: 5000
  download_size: 123027
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- config_name: cross_variable_learning_struct4
  features:
  - name: date
    dtype: int64
  - name: FeatureA_WhiteNoise
    dtype: float64
  - name: FeatureB_Lag24
    dtype: float64
  splits:
  - name: train
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    num_examples: 5000
  download_size: 122857
  dataset_size: 120000
- config_name: datasetlength
  features:
  - name: date
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  - name: Feature1
    dtype: float64
  splits:
  - name: train
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    num_examples: 2064000
  download_size: 30150682
  dataset_size: 33024000
- config_name: longdistance
  features:
  - name: date
    dtype: int64
  - name: Feature1
    dtype: float64
  splits:
  - name: train
    num_bytes: 240000
    num_examples: 15000
  download_size: 127490
  dataset_size: 240000
- config_name: noise
  features:
  - name: date
    dtype: int64
  - name: Feature1
    dtype: float64
  splits:
  - name: train
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    num_examples: 240000
  download_size: 3509672
  dataset_size: 3840000
- config_name: period
  features:
  - name: date
    dtype: int64
  - name: Feature1
    dtype: float64
  splits:
  - name: train
    num_bytes: 800000
    num_examples: 50000
  download_size: 514654
  dataset_size: 800000
- config_name: trend
  features:
  - name: date
    dtype: int64
  - name: Feature1
    dtype: float64
  splits:
  - name: train
    num_bytes: 880000
    num_examples: 55000
  download_size: 742881
  dataset_size: 880000
---

# SynTSBench: A Synthetic Time Series Benchmark

SynTSBench is a comprehensive synthetic time series benchmark dataset designed for evaluating machine learning models on various time series tasks.

## Dataset Structure

The dataset is organized into distinct configurations based on different time series characteristics and column structures:

- **anomaly**: Synthetic time series data from Dataset_generated_anomaly with columns: Feature1, date
- **autocorrelation_long_dependency**: Synthetic time series data from Dataset_generated_autocorrelation-long-dependency with columns: Feature1, date
- **complex_multivariate_struct0**: Synthetic time series data from Dataset_generated_complex_multivariate with columns: Feature1, Feature2, date
- **complex_multivariate_struct1**: Synthetic time series data from Dataset_generated_complex_multivariate with columns: consumer_spending, date, gdp_growth, inflation, interest_rate, unemployment_rate
- **complex_multivariate_struct2**: Synthetic time series data from Dataset_generated_complex_multivariate with columns: beverage_sales, date, ice_cream_sales, rainfall, temperature, umbrella_sales
- **complex_multivariate_struct3**: Synthetic time series data from Dataset_generated_complex_multivariate with columns: Feature1, Feature2, Feature3, date
- **complex_multivariate_struct4**: Synthetic time series data from Dataset_generated_complex_multivariate with columns: date, economic_growth, employment_rate, market_confidence, negative_indicator
- **complex_multivariate_struct5**: Synthetic time series data from Dataset_generated_complex_multivariate with columns: ad_spend, date, sales
- **complex_multivariate_struct6**: Synthetic time series data from Dataset_generated_complex_multivariate with columns: date, demand, price, supply
- **complex_univariate**: Synthetic time series data from Dataset_generated_complex_univariate with columns: Feature1, date
- **cross_variable_learning_struct0**: Synthetic time series data from Dataset_generated_cross-variable-learning with columns: FeatureA_WhiteNoise, FeatureB_Lag48, date
- **cross_variable_learning_struct1**: Synthetic time series data from Dataset_generated_cross-variable-learning with columns: FeatureA_WhiteNoise, FeatureB_Lag10, date
- **cross_variable_learning_struct2**: Synthetic time series data from Dataset_generated_cross-variable-learning with columns: FeatureA_Sin, FeatureB_Noise_0dB, FeatureC_Sum, date
- **cross_variable_learning_struct3**: Synthetic time series data from Dataset_generated_cross-variable-learning with columns: FeatureA_WhiteNoise, FeatureB_Lag5, date
- **cross_variable_learning_struct4**: Synthetic time series data from Dataset_generated_cross-variable-learning with columns: FeatureA_WhiteNoise, FeatureB_Lag24, date
- **datasetlength**: Synthetic time series data from Dataset_generated_datasetlength with columns: Feature1, date
- **longdistance**: Synthetic time series data from Dataset_generated_longdistance with columns: Feature1, date
- **noise**: Synthetic time series data from Dataset_generated_noise with columns: Feature1, date
- **period**: Synthetic time series data from Dataset_generated_period with columns: Feature1, date
- **trend**: Synthetic time series data from Dataset_generated_trend with columns: Feature1, date