Machine Learning for Data Mining

Model training ethics

When you are training the neural network model, never train the model with the whole dataset. We need to hold back some data for testing purposes. This will allow us to test whether the neural network is able to apply what its learned from the training dataset to a new data.

We want the neural network to generalize well to new data and capture the generalities of different types of data, not just little nuances that would then make it sample-specific. Instead, we want the results to be translated to the new data as well. After the model has been trained, the new data can be predicted using the model's experience.