Domino Data Lab

MAY 20, 2021

Insufficient training data in the minority class — In domains where data collection is expensive, a dataset containing 10,000 examples is typically considered to be fairly large. This carries the risk of this modification performing worse than simpler approaches like majority under-sampling. Chawla et al. link] Hall, L.,

Machine Learning 136

Machine Learning Metrics Data mining Knowledge Discovery 136

Domino Data Lab

MAY 8, 2019

The lens of reductionism and an overemphasis on engineering becomes an Achilles heel for data science work. Instead, consider a “full stack” tracing from the point of data collection all the way out through inference. He talked about the risks of reductionism and Descartes’ questionable legacy. Ergo, less interpretable.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

Domino Data Lab

AUGUST 1, 2021

For this demo we’ll use the freely available Statlog (German Credit Data) Data Set, which can be downloaded from Kaggle. This dataset classifies customers based on a set of attributes into two credit risk groups – good or bad. PDPs for the bicycle count prediction model (Molnar, 2009). Ribeiro, M. Guestrin, C.,

Modeling 139

Modeling Deep Learning Machine Learning Knowledge Discovery 139

datapine

DECEMBER 28, 2021

Exclusive Bonus Content: Download Our Free Data Integrity Checklist. Get our free checklist on ensuring data collection and analysis integrity! Misleading statistics refers to the misuse of numerical data either intentionally or by error. Exclusive Bonus Content: Download Our Free Data Integrity Checklist.

Statistics 363

Statistics Advertising Visualization Data mining 363