GRU-based Time-Series Forecasting Model to Predict Household Electric Power Consumption
Problem Statement
Develop a GRU-based time-series forecasting model to predict household electric power consumption using historical electricity usage data and evaluate its performance using MAE and RMSE.
Download Dataset: Household_Power_Consumption.txt
Dataset Description
The dataset contains measurements of electric power consumption in one household, recorded over time.
| Attribute | Description |
|---|---|
| Date | Date of measurement |
| Time | Time of measurement |
| Global_active_power | Household global active power in kilowatts (kW) |
| Global_reactive_power | Household global reactive power in kilowatts |
| Voltage | Average voltage in volts |
| Global_intensity | Average current intensity in amperes |
| Sub_metering_1 | Energy consumption mainly from kitchen appliances |
| Sub_metering_2 | Energy consumption mainly from laundry appliances |
| Sub_metering_3 | Energy consumption mainly from water heater and air conditioner |
For our GRU practical, the main prediction variable will be:
Global_active_power
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