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Explainable systems and Black box systems
White Box vs Black Box
There are two types of AI systems that can be defined
- 1.Explainable systems or White box systems
- 2.Black Box systems
These are the AI systems or Models where one can easily map the input to the output. One knows what is happening during the training phase and how the system makes the appropriate choice.
Examples: Linear Regression and Decision Tree
These are the AI systems or Models where one can not map the input to the output. You do not know what is happening within the system.
Example: Deep Learning and Computer Vision Models