# Look into model recommendation I (AutoML as well)

## Recommend which models to use for training

def recommend_model(dataset):
    """Recommend which models to use for training"""
    THRESHOLD = 0.01
    for column in dataset.columns:
        if 'label' in column:
            if isinstance(column, str):
                return {"recommended_model":"classification"}
                break
            else:
                    num_unique_values = len(dataset[column].unique())
                    threshold = 0.01  #can be changed 
                    num_rows = len(dataset[column])

                    if num_unique_values/num_rows  < threshold :
                            return {"recommended_model":"classification"}
                    else:
                            return {"recommended_model":"regression"}
                    
                    
