Occam's Razor

SEPTEMBER 29, 2009

One of the ultimate excuses for not measuring impact of Marketing campaigns is: "Oh, that's just a branding campaign." It is criminal not to measure your direct response campaigns online. I also believe that a massively under appreciated opportunity exists to truly measure impact of branding campaigns online.

Measurement 128

Measurement Metrics Analytics Marketing 128

Sisense

JANUARY 21, 2020

One of the simplest ways to start exploring your data is to aggregate the metrics you are interested in by their relevant dimensions. A new drug promising to reduce the risk of heart attack was tested with two groups. When the data is combined, it seems that the drug reduces the risk of getting a heart attack.

Testing 104

Testing Risk Data-driven Statistics 104

John Wheeler

NOVEMBER 25, 2020

Integrated risk management (IRM) technology is uniquely suited to address the myriad of risks arising from the current crisis and future COVID-19 recovery. Re-starting business operations will require risk visibility not only across the organization but vertically down through the organization as well. Key Findings.

Marketing 110

Marketing Risk Management Risk Digital Transformation 110

Peter James Thomas

AUGUST 12, 2018

This piece was prompted by both Olaf’s question and a recent article by my friend Neil Raden on his Silicon Angle blog, Performance management: Can you really manage what you measure? It is hard to account for such tweaking in measurement systems. Pertinence and fidelity of metrics developed from Data.

Metrics 49

Metrics Statistics Data Quality Measurement 49

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. return synthetic. Chawla et al.

Machine Learning 136

Machine Learning Metrics Data mining Knowledge Discovery 136

Domino Data Lab

MAY 8, 2019

That’s a risk in case, say, legislators – who don’t understand the nuances of machine learning – attempt to define a single meaning of the word interpret. Visualizations are vital in data science work, with the caveat that the information that they convey may be 4-5 layers of abstraction away from the actual business process being measured.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

Domino Data Lab

AUGUST 1, 2021

Because of its architecture, intrinsically explainable ANNs can be optimised not just on its prediction performance, but also on its explainability metric. This dataset classifies customers based on a set of attributes into two credit risk groups – good or bad. 1 570 0 570 Name: credit, dtype: int64. See Wei et al.

Modeling 139

Modeling Deep Learning Machine Learning Knowledge Discovery 139