I'm encountering an issue where a classifier I'm developing reports validation errors during training that span a wide range of values without consistently decreasing over time. Unfortunately, I'm new ...
Let's say I have two models. One has cumulative lift on test data 4.322578, second 2.84488. The only advantage of the second over the first consists in the quality of having the cumulative lift curve ...
I am training a neural network with time dependent financial data. In order to avoid overfitting I would like to stop the training at the point where my neural network stops improving on a set of ...
I am currently doing a project which involves pothole detection and neural networks. So far, I have an Android phone that reads Accelerometer readings and writes the X,Y,Z Axis aswell as the Amplitude ...