2009 and Knowledge Discovery - Data Leaders Brief

ML internals: Synthetic Minority Oversampling (SMOTE) Technique

Domino Data Lab

MAY 20, 2021

Proceedings of the Fourth International Conference on Knowledge Discovery and Data Mining, 73–79. UCI machine learning repository. link] Fisher, R. The use of multiple measurements in taxonomic problems. Annals of Eugenics, 7(2), 179–188. link] Halevy, A. Norvig, P., & Pereira, F. The unreasonable effectiveness of data.

Machine Learning

Machine Learning Metrics Data mining Knowledge Discovery

Explaining black-box models using attribute importance, PDPs, and LIME

Domino Data Lab

AUGUST 1, 2021

PDPs for the bicycle count prediction model (Molnar, 2009). Courville, Pascal Vincent, Visualizing Higher-Layer Features of a Deep Network, 2009. Conference on Knowledge Discovery and Data Mining, pp. Creating a PDP for our model is fairly straightforward. Ribeiro, M. Guestrin, C., Why should I trust you?: Bahdanau, D.,

Modeling

Modeling Deep Learning Machine Learning Knowledge Discovery

Data Leaders Brief

ML internals: Synthetic Minority Oversampling (SMOTE) Technique

Explaining black-box models using attribute importance, PDPs, and LIME

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