98
edits
Sudeepam
Joined 11 March 2018
→Project Description
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I understand that using Neural Networks may seem like an overkill and that one could think about using traditional data structures like trie, or algorithms like 'edit distance' which are made for exactly these kinds of problems. | I understand that using Neural Networks may seem like an overkill and that one could think about using traditional data structures like trie, or algorithms like 'edit distance' which are made for exactly these kinds of problems. | ||
However, edit distance, while being accurate, would be the slowest approach of the three, and trie, though fast, would not be able to generalize to unknown typographic errors. Neural networks, however, when trained with proper data, would be highly accurate, would generalize to unknown typographic errors, and because of the fact that ultimately '''a 'trained' Neural Network''' will be merged with Octave, this approach will be fast as well. Another disadvantage when using trie that I'd like to mention here is that, if, say, we are unable to arrange a sufficiently large list of common spelling errors, a trie would fail miserably, however, a neural network even in that case, would easily identify letter substitutions and transportations of adjacent letters. | However, edit distance, while being accurate, would be the slowest approach of the three, and trie, though fast, would not be able to generalize to unknown typographic errors. Neural networks, however, when trained with proper data, would be highly accurate, would generalize to unknown typographic errors, and because of the fact that ultimately '''a 'trained' Neural Network''' will be merged with Octave, this approach will be fast as well. Another disadvantage when using trie that I'd like to mention here is that, if, say, we are unable to arrange a sufficiently large list of common spelling errors or if an errors is made while typing the first few characters of the function, a trie would fail miserably, however, a neural network even in that case, would easily identify letter substitutions and transportations of adjacent letters. | ||
This is why, after due consideration, as described above, to me, '''neural networks look like the best solution to minimize the trade-off between speed and accuracy of the feature''' and this is the reason why I have chosen to use them. | This is why, after due consideration, as described above, to me, '''neural networks look like the best solution to minimize the trade-off between speed and accuracy of the feature''' and this is the reason why I have chosen to use them. | ||