GALE aggregates local explanations to reveal global model behavior, showing that LIME's global importance measure is unreliable while the proposed aggregations better capture how features affect predictions.
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Presents YoutubeGraph-Dyn, a multi-modal dynamic graph dataset from YouTube interactions with intra-day snapshots, and benchmarks clustering for community migration plus time series and RNN methods for forecasting non-timestamped attributes.
citing papers explorer
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Global Aggregations of Local Explanations for Black Box models
GALE aggregates local explanations to reveal global model behavior, showing that LIME's global importance measure is unreliable while the proposed aggregations better capture how features affect predictions.
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Tracking Temporal Evolution of Graphs using Non-Timestamped Data
Presents YoutubeGraph-Dyn, a multi-modal dynamic graph dataset from YouTube interactions with intra-day snapshots, and benchmarks clustering for community migration plus time series and RNN methods for forecasting non-timestamped attributes.