diff --git a/README.md b/README.md index 6d6383dcee77f8cf092b4b7a98f8fb176ce9deb1..f4ea8afb55eb9872bfc6afe17ff55c29e013f701 100644 --- a/README.md +++ b/README.md @@ -23,11 +23,25 @@ Here we can conclude that the best K is 5, (if we don't use k = 1) with a perfo ### Maths 1° - + ### Code +All the code can be found in the Python file mlp.py. + +Below, you will find the graph of accuracy as a function of the number of epochs. We used a learning rate of 0.1 and a split ratio of 0.9 between the training and testing datasets. + + + + + +Firstly, we observe that accuracy increases with each epoch. + +However, after 100 epochs, the accuracy is around 16.2%, which is about half the accuracy achieved by the KNN method. + +In conclusion, the MLP method is somewhat disappointing. It might be improved by increasing the number of epochs or adjusting the learning rate. I also observed that the MLP method was faster than the KNN method. +