What is: lift, KPI, robustness, model fitting, design of experiments, 80/20 rule?

Data Science, AI and ML
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What is: lift, KPI, robustness, model fitting, design of experiments, 80/20 rule?

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Lift: lift is a measure of the performance of a targeting model measured against a random choice targeting model; in other words, lift tells you how much better your model is at predicting things than if you had no model.

KPI: stands for Key Performance Indicator, which is a measurable metric used to determine how well a company is achieving its business objectives. Eg. error rate.

Robustness: generally robustness refers to a system’s ability to handle variability and remain effective.

Model fitting: refers to how well a model fits a set of observations.

Design of experiments: also known as DOE, it is the design of any task that aims to describe and explain the variation of information under conditions that are hypothesized to reflect the variable. [4] In essence, an experiment aims to predict an outcome based on a change in one or more inputs (independent variables).

80/20 rule: also known as the Pareto principle; states that 80% of the effects come from 20% of the causes. Eg. 80% of sales come from 20% of customers.