26 lines
1.5 KiB
Markdown
26 lines
1.5 KiB
Markdown
# machineLearning
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R# machine learning library
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+ [softmax](machineLearning/softmax.1)
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+ [raw_samples](machineLearning/raw_samples.1)
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+ [add_samples](machineLearning/add_samples.1) add new training sample collection into the model dataset
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+ [read.ANN_network](machineLearning/read.ANN_network.1)
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+ [load.parallel_ANN](machineLearning/load.parallel_ANN.1)
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+ [as.ANN](machineLearning/as.ANN.1)
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+ [new.ML_model](machineLearning/new.ML_model.1) create a new model dataset
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+ [add](machineLearning/add.1) add new training sample into the model dataset
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+ [ANN.predict](machineLearning/ANN.predict.1)
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+ [normalize](machineLearning/normalize.1)
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+ [create.normalize](machineLearning/create.normalize.1) Create normalization matrix data object for the given ANN training data model
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+ [check.ML_model](machineLearning/check.ML_model.1) check the errors that may exists in the dataset file.
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+ [write.ANN_network](machineLearning/write.ANN_network.1) save a trained ANN network model into a given xml files.
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+ [open.debugger](machineLearning/open.debugger.1) open a file connection to the model debug file.
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+ [ANN.training_model](machineLearning/ANN.training_model.1) create a new ANN training model
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+ [configuration](machineLearning/configuration.1) Apply configuration on the ANN training model.
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+ [input.size](machineLearning/input.size.1)
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+ [output.size](machineLearning/output.size.1)
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+ [set.trainingSet](machineLearning/set.trainingSet.1)
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+ [training](machineLearning/training.1) do ANN model training
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+ [training.ANN](machineLearning/training.ANN.1) do ANN model training
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