Datasets:
File size: 11,427 Bytes
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license: mit
configs:
- config_name: anomaly
data_files:
- split: train
path: anomaly/train-*
- config_name: autocorrelation_long_dependency
data_files:
- split: train
path: autocorrelation_long_dependency/train-*
- config_name: complex_multivariate_struct0
data_files:
- split: train
path: complex_multivariate_struct0/train-*
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path: complex_multivariate_struct1/train-*
- config_name: complex_multivariate_struct2
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path: complex_multivariate_struct2/train-*
- config_name: complex_multivariate_struct3
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path: complex_multivariate_struct3/train-*
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path: complex_multivariate_struct4/train-*
- config_name: complex_multivariate_struct5
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path: complex_multivariate_struct5/train-*
- config_name: complex_multivariate_struct6
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path: complex_multivariate_struct6/train-*
- config_name: complex_univariate
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path: complex_univariate/train-*
- config_name: cross_variable_learning_struct0
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path: cross_variable_learning_struct0/train-*
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path: cross_variable_learning_struct1/train-*
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path: cross_variable_learning_struct2/train-*
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path: cross_variable_learning_struct3/train-*
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path: cross_variable_learning_struct4/train-*
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path: datasetlength/train-*
- config_name: longdistance
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- split: train
path: longdistance/train-*
- config_name: noise
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- 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:
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dtype: float64
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- config_name: longdistance
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dtype: int64
- name: Feature1
dtype: float64
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dtype: int64
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dtype: float64
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- name: date
dtype: int64
- name: Feature1
dtype: float64
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- config_name: trend
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- name: date
dtype: int64
- name: Feature1
dtype: float64
splits:
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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 |