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Insufficient training data in the minority class — In domains where datacollection is expensive, a dataset containing 10,000 examples is typically considered to be fairly large. This carries the risk of this modification performing worse than simpler approaches like majority under-sampling. Chawla et al. link] Ling, C.
This is a knowledge that anyone can get, but it would take much longer than optimal. But still, is there a risk that AI could replace people at their workplace? This is extremely powerful, so literacy in datacollection and data processing will be one of the crucial skills of the future. It’s very likely.
For this demo we’ll use the freely available Statlog (German Credit Data) Data Set, which can be downloaded from Kaggle. This dataset classifies customers based on a set of attributes into two credit risk groups – good or bad. Conference on KnowledgeDiscovery and Data Mining, pp. Ribeiro, M.
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