2011년 12월 21일 수요일 오전 11:01Hi, a quick questions for the data models selection, I’ve got a dataset with around 100 attributes and a class label with binomial value (1 or 0). Could anyone give some suggestion of what type of data mining model will be suitable for the prediction/score the data? Many thanks!
2011년 12월 21일 수요일 오후 2:03Check AdventureWorks - I think it does this with a bit column "Bike Buyer" as I recall - try Decision Trees.
2011년 12월 21일 수요일 오후 3:07
In addition to Doyle's suggestion, Neural Networks works well with binomial value as well. But, since you have 100 input attributes, training the model might take longer that Decision tree. You might want to try both algorithms and see which one works better.
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2011년 12월 21일 수요일 오후 5:23답변자
Decision tree - simple and easy to understand
Neural Networks - powerful but can be slow. Difficult to understand
Logistic regression - good algorithm that works faster than Neural Networks
Naive Bayes - quick and easy to understand
Clustering - quick and easy to understand
Create multiple models and compare their accuracy.
Tatyana Yakushev [PredixionSoftware.com]
- 답변으로 표시됨 stephen huo 2011년 12월 21일 수요일 오후 6:20
2011년 12월 21일 수요일 오후 6:21Many thanks for the suggestions, I probably start with Logistric regression and Neural Network and compare their accuracy. cheers :)