Technology used- Python3, Random forest, Hyperparameter tuning.
fixed.acidity
volatile.acidity
citric.acid
residual.sugar
chlorides
free.sulfur.dioxide
total.sulfur.dioxide
density
pH
sulphates
alcohol
quality (label)
fixed.acidity
volatile.acidity
citric.acid
residual.sugar
chlorides
free.sulfur.dioxide
total.sulfur.dioxide
density
pH
sulphates
alcohol
quality (label)
The final prediction is based on Random Forest Regressor and dumped into Testing and prediction.csv file. Train accuracy is around 0.96 which shows that it has low bias.