project 4: Wine Quality Prediction
Each wine in this dataset is given a "quality" score between 3 and 8. It was a team project. After evaluation of the performance of the algorithm and testing with four different classification models deployed for the analysis. The following conclusion was made: Random forest classification gave the best and least RMSE value of 0.62. This means that, averagely, an error of + or - 0.62 could be obtained from our prediction.
