2017, Forecasting, Knowledge Discovery and Measurement

On the Hunt for Patterns: from Hippocrates to Supercomputers

Ontotext

MAY 18, 2020

These are the so-called supercomputers, led by a smart legion of researchers and practitioners in the fields of data-driven knowledge discovery. The capacity and performance of supercomputers is measured with the so-called FLOPS (floating point operations per second). What are supercomputers and why do we need them?

Knowledge Discovery

Knowledge Discovery Experimentation Data-driven Metadata

ML internals: Synthetic Minority Oversampling (SMOTE) Technique

Domino Data Lab

MAY 20, 2021

This renders measures like classification accuracy meaningless. note that this variant “performs worse than plain under-sampling based on AUC” when tested on the Adult dataset (Dua & Graff, 2017). The use of multiple measurements in taxonomic problems. Indeed, in the original paper Chawla et al. Machine Learning, 57–78.

Machine Learning

Machine Learning Metrics Data mining Knowledge Discovery

Data Leaders Brief

On the Hunt for Patterns: from Hippocrates to Supercomputers

ML internals: Synthetic Minority Oversampling (SMOTE) Technique

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