Documentation
¶
Index ¶
- func KFoldPatternsSplit(patterns []mn.Pattern, k int, shuffle int) [][]mn.Pattern
- func KFoldValidation(neuron *mn.NeuronUnit, patterns []mn.Pattern, epochs int, k int, shuffle int) []float64
- func MLPKFoldValidation(mlp *mn.MultiLayerNetwork, patterns []mn.Pattern, epochs int, k int, ...) []float64
- func MLPRandomSubsamplingValidation(mlp *mn.MultiLayerNetwork, patterns []mn.Pattern, percentage float64, ...) []float64
- func RNNValidation(mlp *mn.MultiLayerNetwork, patterns []mn.Pattern, epochs int, shuffle int) (float64, []float64)
- func RandomSubsamplingValidation(neuron *mn.NeuronUnit, patterns []mn.Pattern, percentage float64, epochs int, ...) []float64
- func TrainTestPatternSplit(patterns []mn.Pattern, percentage float64, shuffle int) (train []mn.Pattern, test []mn.Pattern)
- func TrainTestPatternsSplit(patterns []mn.Pattern, percentage float64, shuffle int) (train []mn.Pattern, test []mn.Pattern)
Constants ¶
This section is empty.
Variables ¶
This section is empty.
Functions ¶
func KFoldPatternsSplit ¶
KFoldPatternsSplit split an array of patterns in k subsets. if shuffle is 0 the function partitions the items maintaining the order otherwise the patterns array is shuffled before partitioning
func KFoldValidation ¶
func KFoldValidation(neuron *mn.NeuronUnit, patterns []mn.Pattern, epochs int, k int, shuffle int) []float64
RandomSubsamplingValidation perform evaluation on neuron algorithm. It returns scores reached for each fold iteration.
func MLPKFoldValidation ¶
func MLPKFoldValidation(mlp *mn.MultiLayerNetwork, patterns []mn.Pattern, epochs int, k int, shuffle int, mapped []string) []float64
RandomSubsamplingValidation perform evaluation on neuron algorithm. It returns scores reached for each fold iteration.
func MLPRandomSubsamplingValidation ¶
func MLPRandomSubsamplingValidation(mlp *mn.MultiLayerNetwork, patterns []mn.Pattern, percentage float64, epochs int, folds int, shuffle int, mapped []string) []float64
It returns scores reached for each fold iteration.
func RNNValidation ¶
func RNNValidation(mlp *mn.MultiLayerNetwork, patterns []mn.Pattern, epochs int, shuffle int) (float64, []float64)
RNNValidation perform evaluation on neuron algorithm.
func RandomSubsamplingValidation ¶
func RandomSubsamplingValidation(neuron *mn.NeuronUnit, patterns []mn.Pattern, percentage float64, epochs int, folds int, shuffle int) []float64
RandomSubsamplingValidation perform evaluation on neuron algorithm. It returns scores reached for each fold iteration.
func TrainTestPatternSplit ¶
func TrainTestPatternSplit(patterns []mn.Pattern, percentage float64, shuffle int) (train []mn.Pattern, test []mn.Pattern)
TrainTestPatternsSplit split an array of patterns in training and testing. if shuffle is 0 the function takes the first percentage items as train and the other as test otherwise the patterns array is shuffled before partitioning
func TrainTestPatternsSplit ¶
func TrainTestPatternsSplit(patterns []mn.Pattern, percentage float64, shuffle int) (train []mn.Pattern, test []mn.Pattern)
TrainTestPatternsSplit split an array of patterns in training and testing. if shuffle is 0 the function takes the first percentage items as train and the other as test otherwise the patterns array is shuffled before partitioning
Types ¶
This section is empty.
Source Files