Accurate Decision Tree Construction

Provided by: International Journal of Computer Science & Engineering Technology (IJCSET)
Topic: Data Management
Format: PDF
Classification is one of the most important techniques in data mining. Decision tree is the most important classification technique in machine learning and data mining. Decision tree classifiers are constructed using training dada sets. Training data sets contain numerical (or continuous) and categorical (or discrete) attributes. Measurement errors are common in any data collection process, particularly when training datasets contain numerical (or continuous) attributes. So, values of numerical attributes contain measurement errors in many training data sets.

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