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ML internals: Synthetic Minority Oversampling (SMOTE) Technique

Domino Data Lab

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. Machine Learning, 57–78.

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How to unlock a scientific approach to change management with powerful data insights

IBM Big Data Hub

Furthermore, this capability can also tackle another stumbling block we face: once you have introduced a change, how do you easily measure its success and adoption? By applying process mining, you can quickly see levels of process compliance right across the organisation and right across the value chain.

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Towards optimal experimentation in online systems

The Unofficial Google Data Science Blog

the weight given to Likes in our video recommendation algorithm) while $Y$ is a vector of outcome measures such as different metrics of user experience (e.g., Taking measurements at parameter settings further from control parameter settings leads to a lower variance estimate of the slope of the line relating the metric to the parameter.

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10 Best Big Data Analytics Tools You Need To Know in 2023

FineReport

Here are some key factors to keep in mind: Understanding business objectives : It is important to identify and understand the business objectives before selecting a big data tool. These objectives should be broken down into measurable analytical goals, and the chosen tool should be able to meet those goals. Top 10 Big Data Tools 1.

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What Is Embedded Analytics?

Jet Global

Users Want to Help Themselves Data mining is no longer confined to the research department. Today, every professional has the power to be a “data expert.” Manage compliance through up-to-the-minute performance measures, workflow automation, and essential regulatory reports. How to measure the value.