The Partial Response Network

by   Paulo J. G. Lisboa, et al.

We propose a method to open the black box of the Multi-Layer Perceptron by inferring from it a simpler and generally more accurate general additive model. The resulting model comprises non-linear univariate and bivariate partial responses derived from the original Multi-Layer Perceptron. The responses are combined using the Lasso and further optimised within a modular structure. The approach is generic and provides a constructive framework to simplify and explain the Multi-Layer Perceptron for any data set, opening the door for validation against prior knowledge. Experimental results on benchmarking datasets indicate that the partial responses are intuitive to interpret and the Area Under the Curve is competitive with Gradient Boosting, Support Vector Machines and Random Forests. The performance improvement compared with a fully connected Multi-Layer Perceptron is attributed to reduced confounding in the second stage of optimisation of the weights. The main limitation of the method is that it explicitly models only up to pairwise interactions. For many practical applications this will be optimal, but where that is not the case then this will be indicated by the performance difference compared to the original model. The streamlined model simultaneously interprets and optimises this frequently used flexible model.


Explicit Computation of Input Weights in Extreme Learning Machines

We present a closed form expression for initializing the input weights i...

Challenging On Car Racing Problem from OpenAI gym

This project challenges the car racing problem from OpenAI gym environme...

Time series modeling with pruned multi-layer perceptron and 2-stage damped least-squares method

A Multi-Layer Perceptron (MLP) defines a family of artificial neural net...

Meteorological time series forecasting with pruned multi-layer perceptron and 2-stage Levenberg-Marquardt method

A Multi-Layer Perceptron (MLP) defines a family of artificial neural net...

Multilayer Perceptron Network Discriminates Larval Zebrafish Genotype using Behaviour

Zebrafish are a common model organism used to identify new disease thera...

Emerging Relation Network and Task Embedding for Multi-Task Regression Problems

Multi-task learning (mtl) provides state-of-the-art results in many appl...

Please sign up or login with your details

Forgot password? Click here to reset