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This data alone does not make any sense unless it’s identified to be related in some pattern. Datamining is the process of discovering these patterns among the data and is therefore also known as KnowledgeDiscovery from Data (KDD). Machine learning provides the technical basis for datamining.
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. Datamining for direct marketing: Problems and solutions. Machine learning for the detection of oil spills in satellite radar images.
The surrogate model is often a simple linear model or a decision tree, which are innately interpretable, so the datacollected from the perturbations and the corresponding class output can provide a good indication on what influences the model’s decision. Conference on KnowledgeDiscovery and DataMining, pp.
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