Difference between revisions of "DETECTING STATISTICAL INTERACTIONS FROM NEURAL NETWORK WEIGHTS"

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Within several areas, regression analysis is essential. However, due to complexity, the only tool left for practitioners are some simple tools based on linear regression. Growth in computational power available, practitioners are now able to use complicated models. Nevertheless, now the problem is not complexity: Interpretability. Neural network mostly exhibits superior predictable power compare to other traditional statistical regression methods. However, it's highly complicated structure simply prevent users to understand the results. In this paper, we are going to present one way of implementing interpretability in neural network.

Revision as of 21:41, 25 November 2018

DETECTING STATISTICAL INTERACTIONS FROM NEURAL NETWORK WEIGHTS

Introduction

Within several areas, regression analysis is essential. However, due to complexity, the only tool left for practitioners are some simple tools based on linear regression. Growth in computational power available, practitioners are now able to use complicated models. Nevertheless, now the problem is not complexity: Interpretability. Neural network mostly exhibits superior predictable power compare to other traditional statistical regression methods. However, it's highly complicated structure simply prevent users to understand the results. In this paper, we are going to present one way of implementing interpretability in neural network.