Type I and Type II Neuron Models Are Selectively Driven by Differential Stimulus Features.
Germán MatoInés SamengoPublished in: Neural Comput. (2008)
Keyphrases
- type ii
- type i error
- predictive power
- classification models
- prior knowledge
- neyman pearson
- neural network
- low level
- machine learning approaches
- abstraction levels
- data driven
- neural model
- statistical models
- statistically significant
- neural models
- machine learning algorithms
- model selection
- upper bound
- classification accuracy
- probabilistic model
- feature vectors
- machine learning