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This project includes the implementation of a neural network MLP, RBF, SOM and Hopfield networks in several popular programming languages. The project also includes examples of the use of neural networks as function approximation and time series prediction. Includes a special program makes it easy to test neural network based on training data and the optimization of the network.
...It then uses this information to partition the original input read set into two subsets, each of which has been enriched for one of the haplotypes. Initial results using this technique have dramatically improved de novo asseblies of such data. The implementation provided here remains partial, and under daily development, and is released as a daily "snapshot" as opposed to a static version.
Program to performing the complete cycle of neural networks analysis: preparing data, choosing neural network (CasCor, MP, LogRegression, PNN), learning of network, monitoring learning state, ROC-analysis, optimization of network parameters using GA.
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