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* [**https://github.com/duyu09/TimeSeries-Forecasting-Dataset/releases/download/v1.0.0/dataset.7z**](https://github.com/duyu09/TimeSeries-Forecasting-Dataset/releases/download/v1.0.0/dataset.7z)
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## Dataset
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* **`ETT`** The Electricity Transformer Temperature (ETT) dataset serves as a critical benchmark for evaluating electric power forecasting. It comprises two years of data collected from two separate counties in China. To analyze the impact of temporal granularity, the dataset is divided into four subsets with different sampling frequencies: ETTh1 and ETTh2 are sampled at 1-hour intervals, while ETTm1 and ETTm2 are sampled at 15-minute intervals. Each data point contains six power load-related features along with a target variable, oil temperature.
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* **`ECL`** The Electricity dataset includes hourly electricity consumption data from 370 clients, providing insights into consumer-level load patterns. Data is collected from 1st January, 2011 with a sampling interval of 15 minutes.
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* [**https://github.com/duyu09/TimeSeries-Forecasting-Dataset/releases/download/v1.0.0/dataset.7z**](https://github.com/duyu09/TimeSeries-Forecasting-Dataset/releases/download/v1.0.0/dataset.7z)
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## Dataset Desc.
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* **`ETT`** The Electricity Transformer Temperature (ETT) dataset serves as a critical benchmark for evaluating electric power forecasting. It comprises two years of data collected from two separate counties in China. To analyze the impact of temporal granularity, the dataset is divided into four subsets with different sampling frequencies: ETTh1 and ETTh2 are sampled at 1-hour intervals, while ETTm1 and ETTm2 are sampled at 15-minute intervals. Each data point contains six power load-related features along with a target variable, oil temperature.
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* **`ECL`** The Electricity dataset includes hourly electricity consumption data from 370 clients, providing insights into consumer-level load patterns. Data is collected from 1st January, 2011 with a sampling interval of 15 minutes.
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