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hello
please help me
I don't understad the value in the distribution table in nave bayes?
Hi @barkhordari55,
Here, you can find an Excel file using the "Golf dataset" to better understand how the Naive Bayes algorithm (without Laplace correction) works :
https://drive.google.com/open?id=12mELZ_SW8fv-VfeRkY-mUjqEUb42ODx6
I hope it helps,
Regards,
Lionel
Hello Lionel, thank you very muchIt was very usefulI have another questionCan you interpret the following results from my RapidMiner?
Helloplease interpret the following results from my nave bayes in RapidMiner?
Difficult to interpret raw results from these screenshots. (I don't know what are your attributes and your target variable)
Maybe I would better understand if you share your dataset(s)...
Hi again @barkhordari55,
I would say (but to be confirmed by your dataset(s)) that you have an imbalanced dataset : You have a (very) big majority of
[target = True] and a minority of [target = False]. So a priori the model you builded consider the prediction = [target = True] whatever
the value of your attributes. It is often the case when a dataset is imbalanced. In fine you have a (relativ) good accuracy but a very bad recall for [target = False] => You are not able to detect and predict the cases [Target = False]
If your primary goal is to detect and predict the case [Target = False], you have to pre-process your data, to increase the performance of your model.
NB : To be confirmed by your dataset(s)
hello lion
thank you very much
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