Advantages of Neural Network & Disadvantages of Neural Network.

 Advantages of Neural Network

• prediction accuracy is generally high
• robust works when training examples contain errors
• output may be discrete, real-valued, or a vector of several discrete or real-valued attributes
• fast evaluation of the learned target function
• High tolerance to noisy data
• Ability to classify untrained patterns
• Well-suited for continuous-valued inputs and outputs
• Successful on a wide array of real-world data
• Algorithms are inherently parallel
• Techniques have recently been developed for the extraction of rules from trained neural networks

Disadvantages of Neural Network

• long training time
• difficult to understand the learned function (weights)
• not easy to incorporate domain knowledge
• Require a number of parameters typically best determined empirically, e.g., the network topology or ``structure."
• Poor interpretability: Difficult to interpret the symbolic meaning behind the learned weights and of ``hidden units" in the network