Decision Tree evaluation Parameters in LSM6DSV16x

FKara.3 · ‎2024-02-20

Hello,

I have a question regarding the evaluation parameters for decision tree results. As you can see in the picture below, the Mean Absolute Error and Root Mean Squared Error are high, but the accuracy is also high. I am confused because I thought that low error and high accuracy are supposed to go hand in hand. Can you please clarify this for me?

Kindly,

Fehmi

Federica Bossi · ‎2024-02-23

Hi @FKara.3 ,

Mean Absolute Error and Root Mean Squared Error are the average accuracy in cross validation. I will point out to the team that the word 'error' can be confusing and to remove it in future releases. Thanks for pointing this out!

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Federica Bossi · ‎2024-02-23

Hi @FKara.3 ,

Mean Absolute Error and Root Mean Squared Error are the average accuracy in cross validation. I will point out to the team that the word 'error' can be confusing and to remove it in future releases. Thanks for pointing this out!

In order to give better visibility on the answered topics, please click on 'Accept as Solution' on the reply which solved your issue or answered your question.

FKara.3 · ‎2024-03-01

Hi @Federica Bossi ,

Perfect.

I have another question. What about Kappa statistic? Why is it low?