The Unofficial Google Data Science Blog

OCTOBER 7, 2015

by HENNING HOHNHOLD, DEIRDRE O'BRIEN, and DIANE TANG In this post we discuss the challenges in measuring and modeling the long-term effect of ads on user behavior. A/B testing is used widely in information technology companies to guide product development and improvements.

Modeling 61

Modeling Experimentation Knowledge Discovery Testing 61

Domino Data Lab

DECEMBER 4, 2020

Once all packages have been imported, we can move on to loading our test data. TIME – time points of measured pain score and plasma concentration (in hrs). There are individual NCA functions that allow us to manually calculate the specific pharmacokinetic measurement of interest. and 3 to 8 hours. pain_df.TIME.==

Metrics 59

Metrics Data Science Knowledge Discovery Measurement 59

The Unofficial Google Data Science Blog

JULY 22, 2020

Another reason to use ramp-up is to test if a website's infrastructure can handle deploying a new arm to all of its users. The website wants to make sure they have the infrastructure to handle the feature while testing if engagement increases enough to justify the infrastructure. We offer two examples where this may be the case.

Experimentation 95

Experimentation Statistics Testing Strategy 95

Domino Data Lab

AUGUST 1, 2021

After forming the X and y variables, we split the data into training and test sets. but it generally relies on measuring the entropy in the change of predictions given a perturbation of a feature. Next, we pick a sample that we want to get an explanation for, say the first sample from our test dataset (sample id 0). Ribeiro, M.

Modeling 139

Modeling Deep Learning Machine Learning Knowledge Discovery 139

Domino Data Lab

MAY 20, 2021

This renders measures like classification accuracy meaningless. Their tests are performed using C4.5-generated 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. Chawla et al.,

Machine Learning 136

Machine Learning Metrics Data mining Knowledge Discovery 136

The Unofficial Google Data Science Blog

JANUARY 14, 2016

Well, it turns out that depending on what it cares to measure, an LSOS might not have enough data. The practical consequence of this is that we can’t afford to be sloppy about measuring statistical significance and confidence intervals. For this purpose, let’s assume we use a t-test for difference between group means.

Experimentation 41

Experimentation Statistics Metrics Measurement 41

The Unofficial Google Data Science Blog

NOVEMBER 4, 2015

Posteriors are useful to understand the system, measure accuracy, and make better decisions. Methods like the Poisson bootstrap can help us measure the variability of $t$, but don’t give us posteriors either, particularly since good high-dimensional estimators aren’t unbiased. Figure 4 shows the results of such a test.

KDD 40

KDD Testing Machine Learning Modeling 40