Self validating model
From here, let’s start thinking about how we can build our Don’t freak out, I’ll explain 😁 What we want is for our value to be checked against a set of rules.
This could be one rule or a thousand, which is why it’s ideal to have rules listed in an array.
Not only is it hard to do it right, but it can also be difficult to implement without making a mess.
When trying to validate data before saving it, it’s easy to pollute methods and violate many programming best practices.
AB - Breast cancer is becoming a leading cause of death among women in the world.
KW - Breast cancer diagnosis KW - Cerebellar model articulation controller KW - Self-validation UR -
This study proposes a self-validation cerebellar model articulation controller (SVCMAC) neural network which can yield high accuracy of predication and low false-negative rate for breast cancer diagnosis.
With its self-validation unit, the SVCMAC neural network has higher classification accuracy than the conventional CMAC neural network.
Let’s try to think about a method that would do it all for us: check if the validation passes, and set the data if it does.
I start with what I want my final code to be and I backward build to make it work.
Here’s how we’d ideally want to setup the model: This would be perfect.
If at least one rule doesn’t pass we need to return statement.
Yet, we’re still explicitly doing two different things in our method.