Documentation ¶
Index ¶
- Constants
- func ApplyThreshold(y *mat.VecDense, t float64) *mat.VecDense
- func Bool(t bool) float64
- func Normalize(xs *mat.Dense) error
- type Fitter
- type LR
- func (lr *LR) Error() float64
- func (lr *LR) Fit(x *mat.Dense, y *mat.VecDense) float64
- func (lr *LR) GobDecode(data []byte) error
- func (lr *LR) GobEncode() ([]byte, error)
- func (lr *LR) Instances() int
- func (lr *LR) MarshalJSON() ([]byte, error)
- func (lr *LR) Predict(x *mat.Dense) *mat.VecDense
- func (lr *LR) UnmarshalJSON(data []byte) error
- func (lr *LR) Weights() []float64
- type NN
- type NNConfig
- type Predictor
Constants ¶
View Source
const ( False = float64(0) True = float64(1) )
Predefined values for true and false.
Variables ¶
This section is empty.
Functions ¶
func ApplyThreshold ¶ added in v0.0.56
ApplyThreshold applies a threshold to the given vector, transforming every value x > t to True and all other values to False. It transforms the input vector and returns it as well.
Types ¶
type LR ¶
LR implements LinearRegression
func (*LR) MarshalJSON ¶
MarshalJSON implements the json.Marshal interface.
func (*LR) UnmarshalJSON ¶
UnmarshalJSON implements the json.Unmarshal interface.
type NN ¶ added in v0.0.57
type NN struct {
// contains filtered or unexported fields
}
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