Predicting-with-Linear-Regression

Statement of the problem

According to the given wine indicators, predict points depending on the description, price, region, and various parameters.

Dataset

In my research, I used a dataset from the Kaggle platform. In the dataset for each product, its description, price, and place of production, are stored origin, sort, and other parameters.

Training the Model

The data were divided into training and testing in a ratio of 7:3. Linear Regression model and a Decision tree were trained using the Scikit-learn library.

Results

Average Linear Regression accuracy = 98.6%

Average Decision Tree accuracy = 98.8%

Conclusion

With the use of decision trees and linear regression, I got two models with sufficiently high accuracy.

Software

Python, Scikit-learn library, NumPy, Pandas