I've had some interesting results from submitting my scores to the Kaggle competition.
On my first attempt, I realized that I had only used a sample set of data to train the model using only 1 epoch. (Am I using this term correctly? Or should it be: "...sample set of data with 1 training epoch.")
My first score was 0.12370.
I decided to run the prediction again, however, this time I switched to the full training set, and ran 3 epochs.
When I submitted my results, the second score was 0.18837!
The accuracy of each model, according to the output in my Jupyter notebook, was ~87% and ~98% respectively.
Given that the reported accuracy is higher for the second model, why would the score from Kaggle be lower?
The only reasons I can think of are:
1. A peculiarity of the scoring system.
2. The first model got "lucky"?