Question on Value of Probability of value 1 or 2 in Neural Network Viewer

Hi, all,

I am confused about the value of Probability of Value 1 or 2 (on a particular attribute value) in Neural Network viewer. E.g. the value of Probability of value 1 is actually very low (the same to the value of Probability of value 2), but why the bar which shows the strength of the probability of these two values are still so strong even stronger than other values of probability of value 1 or 2 based on other attribute values which have a much higher probability of value 1 or 2?

And how does the algorithm calculate the Probability of attribute value in nerual network by the way?

Hope my question is clear.

I am looking forward to hearing from you shortly and thanks a lot in advance.

With best regards,

Yours sincerely,

The scores represent the predicted probability as influenced by a single attribute value.

Here is how the scores are computed:

Assume that the model predicts Bike Buyer (= TRUE or FALSE), based on Home Owner, Commute Distance etc.

A stored procedure creates a "virtual" input, containing, for each row, a single attribute (everything else is missing). Example:

Row 1: (empty) -- all attributes are missing

Row 2: Home Owner = TRUE, everything else is empty (missing)

Row 3: Home Owner = FALSE, everything else is empty (missing)

Row 4: Commute Distance= 0-2 miles, everything else is empty (missing)

Row 5: Commute Distance= 2-4 miles, everything else is empty (missing)

and so on.

For each row in this "virtual" input, the procedure computes PredictProbability(BikeBuyer, 'TRUE') and PredictProbability(BikeBuyer, 'FALSE') as well as Predict(BikeBuyer)

All the results that favor TRUE are then normalized in the 0-100 space

Same for all the results that favor FALSE

So, practically, the Probability of Value 1(or 2) represents a normalized view of the prediction probability for value 1 generated by that input.

Because of the normalization, inputs that predict strongly a value may still have low scores (simply because all other inputs are stronger)

Hope this helps

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Hi,

Thanks for that.

With best regards,

sql

Question on Naive Bayes Viewer

Hi, guys,

I encountered a very weird question on Naive Bayes viewer, that is : one of the attributes does not appeared in Naive Bayes viewer? The original attribute data type is int data type, but then within the mining structure, I change it to discrete with Text as its data type. But the problem is after I trained the model, on the naive bayes viewer, that attribute does not appear at all? Why is that?

I have set the dependency value to be very low to enable all attributes to appear. But only that attribute got the problem?

I am looking forward to hearing from you shortly and thanks a lot in advance.

With best regards,

Yours sincerely

When you change a column's content type or data type (e.g from Integer to Text), BI Developer Studio might mark the column as Ignorable in the mining models that use it.

Could this be the issue you are seeing?

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No, the column is still labelled as input.

|||Was there a specific reason you needed to change the data type to Text? As far as the model is concerned, there's no difference between text and int for discrete attributes.

|||

Hi, Raman,

Thank you very much.

I think I know what you mean now, set the content type to be discrete, but the data type remains as Int? As when I left the data type as Int and content type as Continuous, the model treated all the data as continous. Is that right? Thank you.

With best regards,

Yours sincerely,

|||Correct - if you want ints to be treated as discrete, you just need to make sure that the content type is set correctly (to Discrete or Discretized).

|||

Hi, Raman,

Thanks.

With best regards,

Yours sincerely,

Question on Naive Bayes Viewer

Hi, guys,

I encountered a very weird question on Naive Bayes viewer, that is : one of the attributes does not appeared in Naive Bayes viewer? The original attribute data type is int data type, but then within the mining structure, I change it to discrete with Text as its data type. But the problem is after I trained the model, on the naive bayes viewer, that attribute does not appear at all? Why is that?

I have set the dependency value to be very low to enable all attributes to appear. But only that attribute got the problem?

I am looking forward to hearing from you shortly and thanks a lot in advance.

With best regards,

Yours sincerely

When you change a column's content type or data type (e.g from Integer to Text), BI Developer Studio might mark the column as Ignorable in the mining models that use it.

Could this be the issue you are seeing?

|||

No, the column is still labelled as input.

|||Was there a specific reason you needed to change the data type to Text? As far as the model is concerned, there's no difference between text and int for discrete attributes.

|||

Hi, Raman,

Thank you very much.

I think I know what you mean now, set the content type to be discrete, but the data type remains as Int? As when I left the data type as Int and content type as Continuous, the model treated all the data as continous. Is that right? Thank you.

With best regards,

Yours sincerely,

|||Correct - if you want ints to be treated as discrete, you just need to make sure that the content type is set correctly (to Discrete or Discretized).

|||

Hi, Raman,

Thanks.

With best regards,

Yours sincerely,