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. link] Ling, C.

Machine Learning 136

Machine Learning Metrics Data mining Data Science 136

Data Science 101

OCTOBER 31, 2019

Data mining is the process of discovering these patterns among the data and is therefore also known as Knowledge Discovery from Data (KDD). The models created using these algorithms could be evaluated against appropriate metrics to verify the model’s credibility.

Data mining 77

Data mining KDD Data Science Forecasting 77

The Unofficial Google Data Science Blog

OCTOBER 7, 2015

Nevertheless, A/B testing has challenges and blind spots, such as: the difficulty of identifying suitable metrics that give "works well" a measurable meaning. Henne, Dan Sommerfield, Overall Evaluation Criterion , Proceedings 13th Conference on Knowledge Discovery and Data Mining, 2007. 2] Ron Kohavi, Randal M.

Modeling 63

Modeling Experimentation Knowledge Discovery KDD 63

Domino Data Lab

DECEMBER 4, 2020

Having calculated AUC/AUMC, we can further derive a number of useful metrics like: Total clearance of the drug from plasma. We can now pass the preprocessed data to the Pumas NCAReport function, which calculates a wide range of relevant NCA metrics. We can merge all the metrics in a separate DataFrame for further analysis.

Metrics 59

Metrics Data Science Knowledge Discovery Measurement 59

The Unofficial Google Data Science Blog

JANUARY 14, 2016

The LSOS may do this by exposing a random group of users to the new design and compare them to a control group, and then analyze the effect on important user engagement metrics, such as bounce rate, time to first action, or number of experiences deemed positive. In addition to a suitable metric, we must also choose our experimental unit.

Experimentation 42

Experimentation Statistics Metrics Measurement 42

The Unofficial Google Data Science Blog

FEBRUARY 29, 2016

Variance reduction through conditioning Suppose, as an LSOS experimenter, you find that your key metric varies a lot by country and time of day. And since the metric average is different in each hour of day, this is a source of variation in measuring the experimental effect. Obviously, this doesn’t have to be true.

Experimentation 41

Experimentation Statistics Metrics Measurement 41

Ontotext

APRIL 4, 2019

They have different metrics for judging whether some content is interesting or not. Economy.bg: But doesn’t this algorithm put us in an information bubble by filtering the content for us? Milena Yankova : That’s a very interesting question. The Financial Times has a special department for monitoring people’s behavior.

Recreation/Entertainment 76

Recreation/Entertainment Testing Enterprise Knowledge Discovery 76