… In this thesis, the concept of the error surface is explored using three related methods. Firstly…
method for visualizing the learning trajectory followed by an algorithm on the error surface. It …

… using visualization and exploratory techniques. This work focuses primarily on the dynamics
of learning algorithms, the structure of the error surface … The model is especially useful in an …

… model therefore not well understood [7], but the practice of constructing the best model is also
… Considering classification error surface, the discrete nature of this error measurement has …

… It was reported that re-constructive error surface for a … The error function for the final
layer activation is nearly a flat … cost of comprehension through visualization of procedures/equations …

… using a multi-layer perceptron (MLP), is to use a number of … , the SLP cannot give an
error free classification of the training … Visualization of nearly perfect classification for different …

… Multi-layer perceptron artificial neural networks are used extensively in hydrological and
water resources modelling. … in the error surface can be identified for all models with different …

… To describe and visualize an optimization algorithm (which performs an iterative, guided
search … The Multi-layer Perceptron (MLP) [10] is the standard feedforward neural network model …

… LSE is compared to a multi-layer perceptron in the first … Visualization of the error-curve
resilience against noise while … If Er RMN, we apply this to the elevation of each error surface (ie, …

… LSE is compared to a multi-layer perceptron in the first … Visualization of the error-curve
resilience against noise while … If Er RMN, we apply this to the elevation of each error surface (ie, …