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The objective of this article's study was to explore the potential of DT induction to create better models for the detection of CM, using sensor data collected at farms milking automatically. DT induction was used to classify whether a cow suffers from CM or not. The reason Kamphuis et al. used DT to address the problem is that the sensor data was incomprehensive, and the low prevalence of CM has let to predominantly uneven data making the construction of models even more difficult. Given its strength, DT was the best technique to discover new information in large amounts of fragmented (historical) data.
Please identify the strength and weakness, as well as significant implications, of the decision tree (DT) reduction method used in this academic article. Extensive research is less significant to insightful and critical interpretation.