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Feature Importance

42 papers with code ยท Methodology

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Peri-Diagnostic Decision Support Through Cost-Efficient Feature Acquisition at Test-Time

31 Mar 2020

Computer-aided diagnosis (CADx) algorithms in medicine provide patient-specific decision support for physicians.

FEATURE IMPORTANCE

A copula-based visualization technique for a neural network

27 Mar 2020

Interpretability of machine learning is defined as the extent to which humans can comprehend the reason of a decision.

DECISION MAKING FEATURE IMPORTANCE

From unbiased MDI Feature Importance to Explainable AI for Trees

26 Mar 2020

We attempt to give a unifying view of the various recent attempts to (i) improve the interpretability of tree-based models and (ii) debias the the default variable-importance measure in random Forests, Gini importance.

FEATURE IMPORTANCE

TRACER: A Framework for Facilitating Accurate and Interpretable Analytics for High Stakes Applications

24 Mar 2020

In high stakes applications such as healthcare and finance analytics, the interpretability of predictive models is required and necessary for domain practitioners to trust the predictions.

FEATURE IMPORTANCE TIME SERIES

Towards Ground Truth Evaluation of Visual Explanations

16 Mar 2020

We further introduce two straightforward metrics to evaluate explanations in this setup, and compare their outcomes to standard pixel perturbation using a Relation Network model and three decomposition-based explanation methods: Gradient x Input, Integrated Gradients and Layer-wise Relevance Propagation.

FEATURE IMPORTANCE QUESTION ANSWERING VISUAL QUESTION ANSWERING

Channel Pruning Guided by Classification Loss and Feature Importance

15 Mar 2020

In this work, we propose a new layer-by-layer channel pruning method called Channel Pruning guided by classification Loss and feature Importance (CPLI).

FEATURE IMPORTANCE

A Matlab Toolbox for Feature Importance Ranking

10 Mar 2020

Moreover, the toolbox is evaluated on a database of 163 ultrasound images.

FEATURE IMPORTANCE FEATURE SELECTION

What went wrong and when? Instance-wise Feature Importance for Time-series Models

5 Mar 2020

Our method is inexpensive, model agnostic, and can be used with arbitrarily complex time series models and predictors.

FEATURE IMPORTANCE TIME SERIES

Understanding the Prediction Mechanism of Sentiments by XAI Visualization

3 Mar 2020

The present work aimed to gain an understanding of a machine learning model's prediction mechanism by visualizing the effect of sentiments extracted from online hotel reviews with explainable AI (XAI) methodology.

FEATURE IMPORTANCE

What Emotions Make One or Five Stars? Understanding Ratings of Online Product Reviews by Sentiment Analysis and XAI

29 Feb 2020

The current work analyzed these online reviews by sentiment analysis and used the extracted sentiments as features to predict the product ratings by several machine learning algorithms.

FEATURE IMPORTANCE SENTIMENT ANALYSIS