Multivariate Time Series
**Problem:** You are given a multivariate time series dataset with multiple features. Your task is to forecast the future values of each feature using a suitable algorithm.
**Example:** Suppose we have a dataset with two features: temperature and humidity. We want to forecast the temperature and humidity values for the next 10 days.
**Constraints:** The dataset has 365 days of historical data, and the forecasting horizon is 10 days. You should use a suitable algorithm to handle the multivariate nature of the dataset.
Test Cases
Test Case 1
Input:
[[1,2,3,4,5,6,7,8,9,10,11,12], [13,14,15,16,17,18,19,20,21,22,23,24]]Expected:
[[12.5,13.5,14.5,15.5,16.5,17.5,18.5,19.5,20.5,21.5,22.5,23.5],[24.5,25.5,26.5,27.5,28.5,29.5,30.5,31.5,32.5,33.5,34.5,35.5]]Test Case 2
Input:
[[1,2,3,4,5,6,7,8,9,10,11,12], [13,14,15,16,17,18,19,20,21,22,23,24]]Expected:
[[12.5,13.5,14.5,15.5,16.5,17.5,18.5,19.5,20.5,21.5,22.5,23.5],[24.5,25.5,26.5,27.5,28.5,29.5,30.5,31.5,32.5,33.5,34.5,35.5]]+ 3 hidden test cases