Remove 2001 Remove 2017 Remove Measurement Remove Visualization
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ML internals: Synthetic Minority Oversampling (SMOTE) Technique

Domino Data Lab

This renders measures like classification accuracy meaningless. Figure 3 shows visual explanation of how SMOTE generates synthetic observations in this case. note that this variant “performs worse than plain under-sampling based on AUC” when tested on the Adult dataset (Dua & Graff, 2017). References. link] Chawla, N.

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Themes and Conferences per Pacoid, Episode 8

Domino Data Lab

Network security mushrooms with VPNs, IDS , gateways, various bump-in-the-wire solutions, SIMS tying all the anti-intrusion measures within the perimeter together, and so on. My read of that narrative arc is that some truly weird tensions showed up circa 2001: Arguably, it’s the heyday of DW+BI. credit cards). Data is on the move.

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Themes and Conferences per Pacoid, Episode 12

Domino Data Lab

Their approach is to bombard “organoid” mini brains living in vats with potential cancer meds, to measure the meds’ relative effects. He’s been out of Wolfram for a while and writing exquisite science books including Elements: A Visual Explanation of Every Known Atom in the Universe and Molecules: The Architecture of Everything.