Dummy Data:
UniqueNo. | Count19 | Count20 | Count21 |
---|---|---|---|
ABC123 | 2 | 4 | 2 |
DEF456 | 1 | 3 | 3 |
The column 'UniqueNo' is the unique identifier for which the values correspond to. The columns 'Count19', 'Count20', 'Count21' are values corresponding to each UniqueNo. They are for the years of 2019, 2020, 2021 respectively.
The df is 89 rows long so the data is extremely low.
I need to use a model that can predict atleast over 80% for this.
I've tried LinearRegression, RandomForest, DecisionTree and LSTM but to no avail. (The rmse and mse eval metrics returned terrible values)