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ML internals: Synthetic Minority Oversampling (SMOTE) Technique

Domino Data Lab

Insufficient training data in the minority class — In domains where data collection is expensive, a dataset containing 10,000 examples is typically considered to be fairly large. In their 2002 paper Chawla et al. Figure 3 shows visual explanation of how SMOTE generates synthetic observations in this case.

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A history of tech adaptation for today’s changing business needs

CIO Business Intelligence

The first was becoming one of the first research companies to move its panels and surveys online, reducing costs and increasing the speed and scope of data collection. Its digital transformation process can be divided into several stages, according to Mohammed, each with its own objectives and challenges.

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IT leaders weigh up AI’s role to improve data management

CIO Business Intelligence

The data is then re-transported when the line is available. This doesn’t detract from the fact it’s a very advanced clinical data collection system since it’s digital, in real time, and secure because the data is encrypted on VPN and sent to Emergency’s central data center in Milan.