The Conversion Prediction zone is where the prediction of the conversion model score is created. More complete details about this model are available [here](saved_model:rgRmSDeu).

![Screenshot 2024-01-16 at 10.07.48.png](32ZKxHVv8Slx)

The [classification model](saved_model:rgRmSDeu) first orders the training dataset by the lead creation date column. The model is then trained on the first 80% of the data points in the [train dataset](dataset:lead_information_train_data_prepared) and tested on the remaining 20%. 

The [score recipe](recipe:score_lead_information_score_data_prepared) is used to apply the classification model to the dataset containing the values to predict ([lead_information_score_data_prepared](dataset:lead_information_score_data_prepared)) and generate the predicted values. 

The [evaluation recipe](recipe:evaluate_on_test_set) gathers the predictions made on the test set in order to calculate the expected conversion rate in the following flow zone. 


