A Sensitivity Analysis of (and Practitioners' Guide to) Convolutional Neural Networks for Sentence Classification

by   Ye Zhang, et al.
The University of Texas at Austin

Convolutional Neural Networks (CNNs) have recently achieved remarkably strong performance on the practically important task of sentence classification (kim 2014, kalchbrenner 2014, johnson 2014). However, these models require practitioners to specify an exact model architecture and set accompanying hyperparameters, including the filter region size, regularization parameters, and so on. It is currently unknown how sensitive model performance is to changes in these configurations for the task of sentence classification. We thus conduct a sensitivity analysis of one-layer CNNs to explore the effect of architecture components on model performance; our aim is to distinguish between important and comparatively inconsequential design decisions for sentence classification. We focus on one-layer CNNs (to the exclusion of more complex models) due to their comparative simplicity and strong empirical performance, which makes it a modern standard baseline method akin to Support Vector Machine (SVMs) and logistic regression. We derive practical advice from our extensive empirical results for those interested in getting the most out of CNNs for sentence classification in real world settings.


A Sensitivity Analysis of Attention-Gated Convolutional Neural Networks for Sentence Classification

Recently, Attention-Gated Convolutional Neural Networks (AGCNNs) perform...

Visual Explanations From Deep 3D Convolutional Neural Networks for Alzheimer's Disease Classification

We develop three efficient approaches for generating visual explanations...

IEA: Inner Ensemble Average within a convolutional neural network

Ensemble learning is a method of combining multiple trained models to im...

Classifying Graphs as Images with Convolutional Neural Networks

The task of graph classification is currently dominated by graph kernels...

Active Discriminative Text Representation Learning

We propose a new active learning (AL) method for text classification wit...

On Binary Classification with Single-Layer Convolutional Neural Networks

Convolutional neural networks are becoming standard tools for solving ob...

Vector Field Neural Networks

This work begins by establishing a mathematical formalization between di...

Code Repositories


pytorch Convolutional Networks for Sentence Classification - http://www.aclweb.org/anthology/D14-1181

view repo


A CNN text classification example made using tensorflow

view repo

Please sign up or login with your details

Forgot password? Click here to reset