Documentation
¶
Index ¶
- func CalculateAccuracy(predictions, targets [][]float64) float64
- func CalculateMean(values []float64) float64
- func CalculateStdDev(values []float64) float64
- func FormatDuration(d time.Duration) string
- func InitializeBiases(size int) []float64
- func InitializeWeights(rows, cols int) [][]float64
- func LoadModel(filename string, model interface{}) error
- func MatrixMultiply(a [][]float64, b [][]float64) [][]float64
- func MatrixTranspose(matrix [][]float64) [][]float64
- func MinMaxNormalize(data [][]float64) [][]float64
- func NormalizeData(data [][]float64) [][]float64
- func OuterProduct(a, b []float64) [][]float64
- func PrintNetworkSummary(layerSizes []int, activationFunctions []string)
- func PrintProgress(epoch, totalEpochs int, loss float64)
- func SaveModel(model interface{}, filename string) error
- func SecureRandom() float64
- func ShuffleData(data, targets [][]float64) ([][]float64, [][]float64)
- func SplitData(data, targets [][]float64, validationRatio float64) ([][]float64, [][]float64, [][]float64, [][]float64)
- func VectorAdd(a, b []float64) []float64
- func VectorMultiply(a, b []float64) []float64
- func VectorScale(vector []float64, scalar float64) []float64
- func VectorSubtract(a, b []float64) []float64
Constants ¶
This section is empty.
Variables ¶
This section is empty.
Functions ¶
func CalculateAccuracy ¶
CalculateAccuracy calculates classification accuracy
func CalculateMean ¶
CalculateMean calculates the mean of a slice of float64 values
func CalculateStdDev ¶
CalculateStdDev calculates the standard deviation of a slice of float64 values
func FormatDuration ¶
FormatDuration formats a duration in a human-readable way
func InitializeBiases ¶
InitializeBiases initializes biases with small random values
func InitializeWeights ¶
InitializeWeights initializes weights with Xavier/Glorot initialization
func MatrixMultiply ¶
MatrixMultiply performs matrix multiplication: result = a * b
func MatrixTranspose ¶
MatrixTranspose transposes a matrix
func MinMaxNormalize ¶
MinMaxNormalize normalizes data to [0, 1] range
func NormalizeData ¶
NormalizeData normalizes data using z-score normalization
func OuterProduct ¶
OuterProduct computes the outer product of two vectors
func PrintNetworkSummary ¶
PrintNetworkSummary prints a summary of the neural network architecture
func PrintProgress ¶
PrintProgress prints training progress with a progress bar
func SecureRandom ¶
func SecureRandom() float64
SecureRandom generates a cryptographically secure random float64 between -1 and 1
func ShuffleData ¶
ShuffleData shuffles the data and targets together
func SplitData ¶
func SplitData(data, targets [][]float64, validationRatio float64) ([][]float64, [][]float64, [][]float64, [][]float64)
SplitData splits data into training and validation sets
func VectorMultiply ¶
VectorMultiply multiplies two vectors element-wise
func VectorScale ¶
VectorScale scales a vector by a scalar
func VectorSubtract ¶
VectorSubtract subtracts two vectors element-wise
Types ¶
This section is empty.
Source Files