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#Org.neuroph.util Classes and Interfaces - 46 results found.
| Name | Description | Type | Package | Framework |
| Benchmark | This class is main benchmark driver. | Class | org.neuroph.util.benchmark | Neuroph |
| BenchmarkSample | This is an example how to use Neuroph microbenchmarking frameworkAuthor:Zoran Sevarac | Class | org.neuroph.util.benchmark | Neuroph |
| BenchmarkTask | This class is an abstract base class for specific microbenchmarking tasksAuthor:Zoran Sevarac | Class | org.neuroph.util.benchmark | Neuroph |
| BenchmarkTaskResults | This class holds benchmarking results, elapsed times for all iterations and various statistics min, max, avg times and standard deviation | Class | org.neuroph.util.benchmark | Neuroph |
| ConnectionFactory | Provides methods to connect neurons by creating Connection objects. | Class | org.neuroph.util | Neuroph |
| DecimalScaleNormalizer | Decimal scaling normalization method, which normalize data by moving decimal point in regard to max element in training set (by columns) Normalization is | Class | org.neuroph.util.data.norm | Neuroph |
| DistortRandomizer | This class provides distort randomization technique, which distorts existing weight values using specified distortion factor. | Class | org.neuroph.util.random | Neuroph |
| FileInputAdapter | Class | org.neuroph.util.io | Neuroph | |
| FileOutputAdapter | Class | org.neuroph.util.io | Neuroph | |
| FileUtils | Utility methods for working with files. | Class | org.neuroph.util | Neuroph |
| GaussianRandomizer | This class provides Gaussian randomization technique using Box Muller method. | Class | org.neuroph.util.random | Neuroph |
| InputAdapter | Interface for reading neural network inputs from various data sources. | Interface | org.neuroph.util.io | Neuroph |
| InputStreamAdapter | Class | org.neuroph.util.io | Neuroph | |
| IOHelper | This class is helper for feeding neural network with data using some InputAdapter and writing network output using OutputAdapter | Class | org.neuroph.util.io | Neuroph |
| JDBCInputAdapter | Class | org.neuroph.util.io | Neuroph | |
| JDBCOutputAdapter | Class | org.neuroph.util.io | Neuroph | |
| LayerFactory | Provides methods to create instance of a Layer with specifed number of neurons and neuron's properties. | Class | org.neuroph.util | Neuroph |
| MaxMinNormalizer | MaxMin normalization method, which normalize data in regard to min and max elements in training set (by columns) Normalization is done according to formula: | Class | org.neuroph.util.data.norm | Neuroph |
| MaxNormalizer | Max normalization method, which normalize data in regard to max element in training set (by columns) Normalization is done according to formula: | Class | org.neuroph.util.data.norm | Neuroph |
| MyBenchmarkTask | This class is example of custom benchmarking task for Multi Layer Perceptorn network Note that this benchmark only measures the speed at implementation level - the | Class | org.neuroph.util.benchmark | Neuroph |
| NeuralNetworkCODEC | A CODEC encodes and decodes neural networks, much like the more standard definition of a CODEC encodes and decodes audio/video. | Class | org.neuroph.util | Neuroph |
| NeuralNetworkFactory | Provides methods to create various neural networks. | Class | org.neuroph.util | Neuroph |
| NeuralNetworkType | enum NeuralNetworkTypeContains neural network types and labels. | Class | org.neuroph.util | Neuroph |
| NeuronFactory | Provides methods to create customized instances of Neurons. | Class | org.neuroph.util | Neuroph |
| NeuronProperties | Represents properties of a neuron. | Class | org.neuroph.util | Neuroph |
| Neuroph | Class | org.neuroph.util | Neuroph | |
| NeurophArrayList | Resizable-array implementation of the List interface. | Class | org.neuroph.util | Neuroph |
| NeurophInputException | This exception is thrown when error occurs when reading input using some InputAdapterAuthor:Zoran Sevarac See Also:InputAdapter, | Class | org.neuroph.util.io | Neuroph |
| NeurophOutputException | This exception is thrown when some error occurs when writing neural network output using some output adapter. | Class | org.neuroph.util.io | Neuroph |
| NguyenWidrowRandomizer | This class provides NguyenWidrow randmization technique, which gives very good results for Multi Layer Perceptrons trained with back propagation family of learning rules. | Class | org.neuroph.util.random | Neuroph |
| Normalizer | Interface for data set normalization methods. | Interface | org.neuroph.util.data.norm | Neuroph |
| OutputAdapter | Interface for writing neural network outputs to some destination. | Interface | org.neuroph.util.io | Neuroph |
| OutputStreamAdapter | Class | org.neuroph.util.io | Neuroph | |
| PluginBase | Base class for all neural network plugins. | Class | org.neuroph.util.plugins | Neuroph |
| Properties | Represents a general set of properties for neuroph objectsAuthor:Zoran Sevarac See Also:Serialized Form | Class | org.neuroph.util | Neuroph |
| RangeNormalizer | This class does normalization of a data set to specified rangeAuthor:Zoran Sevarac | Class | org.neuroph.util.data.norm | Neuroph |
| RangeRandomizer | This class provides ranged weights randomizer, which randomize weights in specified [min, max] range. | Class | org.neuroph.util.random | Neuroph |
| Sampling | Interface for data set sampling methods. | Interface | org.neuroph.util.data.sample | Neuroph |
| Stopwatch | A class to help benchmark code, it simulates a real stop watch. | Class | org.neuroph.util.benchmark | Neuroph |
| SubSampling | This class provides subsampling of a data set, and creates two subsets of a given data set - for training and testing. | Class | org.neuroph.util.data.sample | Neuroph |
| TrainingSetImport | Handles training set importsAuthor:Zoran Sevarac, Ivan Nedeljkovic, Kokanovic Rados | Class | org.neuroph.util | Neuroph |
| TransferFunctionType | enum TransferFunctionTypeContains transfer functions types and labels. | Class | org.neuroph.util | Neuroph |
| URLInputAdapter | Class | org.neuroph.util.io | Neuroph | |
| URLOutputAdapter | Class | org.neuroph.util.io | Neuroph | |
| VectorParser | Provides methods to parse strings as Integer or Double vectors. | Class | org.neuroph.util | Neuroph |
| WeightsRandomizer | Basic weights randomizer, iterates and randomizes all connection weights in network. | Class | org.neuroph.util.random | Neuroph |