中殿贝叶斯

barkhordari55

hello

please help me

I don't understad the value in the distribution table in nave bayes?

lionelderkrikor

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

barkhordari55

Hello Lionel, thank you very much
It was very useful
I have another question
Can you interpret the following results from my RapidMiner?

barkhordari55

barkhordari55

Hello
please interpret the following results from my nave bayes inRapidMiner?

lionelderkrikor

Hi@barkhordari55,

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)...

Regards,

Lionel

lionelderkrikor

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]

如果你的主要目标to detect and predict the case [Target = False], you have to pre-process your data, to increase the performance of your model.

Regards,

Lionel

NB : To be confirmed by your dataset(s)

barkhordari55

hello lion

thank you very much