Domino Data Lab

MAY 20, 2021

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. Chawla et al. link] Fisher, R.

Machine Learning 136

Machine Learning Metrics Data mining Knowledge Discovery 136

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). See Wei et al.

Modeling 139

Modeling Deep Learning Machine Learning Knowledge Discovery 139

datapine

DECEMBER 28, 2021

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% Drinking tea increases diabetes by 50%, and baldness raises the cardiovascular disease risk up to 70%!

Statistics 363

Statistics Advertising Visualization Data mining 363