United-States-dollar-Russian-rub-prediction

Problem Statement

We are given with historical Data from Sep 14, 2001 until today of the USD to RUB exchange. In this prediction, we are going to see how much the USD / RUB exchange was affected due to Russia's Invasion of Ukraine

Dataset

The dataset used is the United States dollar / Russian ruble - Historical from Kaggle (https://www.kaggle.com/datasets/fedesoriano/usd-rub-historical-data?resource=download). Attribute Information

1. Date
2. Price
3. Open
4. High
5. Low
6. Change %

Models Used

Linear Regression: This model is most useful in data which is linearly correlated. It simply finds the "Best fit coefficients" by using the standard linear regression formula.

Support Vector Machine: This model is also very useful when the data is linearly correlated. Although, SVMs are capable of projecting the data into greater dimensions to find out better patterns.

Decision Tree Classifier: This model identifies the most informative attribute at every level and uses it to make a tree. The final tree can then be used as a simple if-else statement to identify the final prediction.