Remove 2009 Remove Data mining Remove Measurement
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ML internals: Synthetic Minority Oversampling (SMOTE) Technique

Domino Data Lab

Working with highly imbalanced data can be problematic in several aspects: Distorted performance metrics — In a highly imbalanced dataset, say a binary dataset with a class ratio of 98:2, an algorithm that always predicts the majority class and completely ignores the minority class will still be 98% correct. Dua, D., & Graff, C.

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Mobile Marketing 2015: Rethink Customer Acquisition, Intent Targeting

Occam's Razor

2009 was the year of mobile. If your company has a non-stinky mobile website and mobile app then congratulations: you have successfully solved the problem of 2009! I'm sure you are impressed at the data mining and intent targeting efforts of TripIt. Measurement? Everything described above is measureable.

Marketing 146
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Explaining black-box models using attribute importance, PDPs, and LIME

Domino Data Lab

but it generally relies on measuring the entropy in the change of predictions given a perturbation of a feature. 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.

Modeling 139
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Misleading Statistics Examples – Discover The Potential For Misuse of Statistics & Data In The Digital Age

datapine

These controlling measures are essential and should be part of any experiment or survey – unfortunately, that isn’t always the case. A 2009 investigative survey by Dr. Daniele Fanelli from The University of Edinburgh found that 33.7% This means that there is no definable justification for the placement of the visible measurement lines.