click

package
v0.2.6 Latest Latest
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 Go to latest Published: Sep 26, 2021 License: Apache-2.0 Imports: 20 Imported by: 0

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Index

Constants

This section is empty.

Variables

This section is empty.

Functions

func AUC added in v0.2.5 

func AUC(posPrediction, negPrediction []float32) float32

func Accuracy added in v0.2.5 

func Accuracy(posPrediction, negPrediction []float32) float32

func EncodeModel 

func EncodeModel(m FactorizationMachine) ([]byte, error)

func LoadLibFMFile 

func LoadLibFMFile(path string) (features [][]int32, values [][]float32, targets base.Floats, maxLabel int32, err error)

LoadLibFMFile loads libFM format file.

func Precision added in v0.2.5 

func Precision(posPrediction, negPrediction []float32) float32

func Recall added in v0.2.5 

func Recall(posPrediction, _ []float32) float32

Types

type BaseFactorizationMachine 

type BaseFactorizationMachine struct {
	model.BaseModel
	Index UnifiedIndex
}

func (*BaseFactorizationMachine) Init 

func (b *BaseFactorizationMachine) Init(trainSet *Dataset)

type Dataset 

type Dataset struct {
	Index UnifiedIndex

	UserFeatures [][]int32 // features of users
	ItemFeatures [][]int32 // features of items

	Users       base.Integers
	Items       base.Integers
	CtxFeatures [][]int32
	CtxValues   [][]float32
	NormValues  base.Floats
	Target      base.Floats

	PositiveCount int
	NegativeCount int
}

Dataset for click-through-rate models.

func LoadDataFromBuiltIn 

func LoadDataFromBuiltIn(name string) (train, test *Dataset, err error)

LoadDataFromBuiltIn loads built-in dataset.

func (*Dataset) Count 

func (dataset *Dataset) Count() int

Count returns the number of samples.

func (*Dataset) Get 

func (dataset *Dataset) Get(i int) ([]int32, []float32, float32)

Get returns the i-th sample.

func (*Dataset) ItemCount 

func (dataset *Dataset) ItemCount() int

ItemCount returns the number of items.

func (*Dataset) Split 

func (dataset *Dataset) Split(ratio float32, seed int64) (*Dataset, *Dataset)

Split a dataset to training set and test set.

func (*Dataset) UserCount 

func (dataset *Dataset) UserCount() int

UserCount returns the number of users.

type FM 

type FM struct {
	BaseFactorizationMachine
	// Model parameters
	V         [][]float32
	W         []float32
	B         float32
	MinTarget float32
	MaxTarget float32
	Task      FMTask
	// contains filtered or unexported fields
}

func NewFM 

func NewFM(task FMTask, params model.Params) *FM

func (*FM) Clear 

func (fm *FM) Clear()

func (*FM) Fit 

func (fm *FM) Fit(trainSet, testSet *Dataset, config *FitConfig) Score

func (*FM) GetParamsGrid 

func (fm *FM) GetParamsGrid() model.ParamsGrid

func (*FM) Init 

func (fm *FM) Init(trainSet *Dataset)

func (*FM) InternalPredict 

func (fm *FM) InternalPredict(features []int32, values []float32) float32

func (*FM) Invalid 

func (fm *FM) Invalid() bool

func (*FM) Predict 

func (fm *FM) Predict(userId, itemId string, userLabels, itemLabels []string) float32

func (*FM) SetParams 

func (fm *FM) SetParams(params model.Params)

type FMTask 

type FMTask string
const (
	FMClassification FMTask = "c"
	FMRegression     FMTask = "r"
)

type FactorizationMachine 

type FactorizationMachine interface {
	model.Model
	Predict(userId, itemId string, userLabels, itemLabels []string) float32
	InternalPredict(x []int32, values []float32) float32
	Fit(trainSet *Dataset, testSet *Dataset, config *FitConfig) Score
}

func Clone 

func Clone(m FactorizationMachine) FactorizationMachine

Clone a model with deep copy.

func DecodeModel 

func DecodeModel(buf []byte) (FactorizationMachine, error)

type FitConfig 

type FitConfig struct {
	Jobs    int
	Verbose int
	Tracker model.Tracker
}

func NewFitConfig 

func NewFitConfig() *FitConfig

func (*FitConfig) LoadDefaultIfNil 

func (config *FitConfig) LoadDefaultIfNil() *FitConfig

func (*FitConfig) SetJobs 

func (config *FitConfig) SetJobs(nJobs int) *FitConfig

func (*FitConfig) SetTracker added in v0.2.4 

func (config *FitConfig) SetTracker(tracker model.Tracker) *FitConfig

func (*FitConfig) SetVerbose added in v0.2.5 

func (config *FitConfig) SetVerbose(verbose int) *FitConfig

type ModelSearcher 

type ModelSearcher struct {
	// contains filtered or unexported fields
}

ModelSearcher is a thread-safe click model searcher.

func NewModelSearcher 

func NewModelSearcher(nEpoch, nTrials, nJobs int) *ModelSearcher

NewModelSearcher creates a thread-safe personal ranking model searcher.

func (*ModelSearcher) Fit 

func (searcher *ModelSearcher) Fit(trainSet, valSet *Dataset, tracker model.Tracker, runner model.Runner) error

func (*ModelSearcher) GetBestModel 

func (searcher *ModelSearcher) GetBestModel() (FactorizationMachine, Score)

GetBestModel returns the best click model with its score.

type ParamsSearchResult 

type ParamsSearchResult struct {
	BestScore  Score
	BestModel  FactorizationMachine
	BestParams model.Params
	BestIndex  int
	Scores     []Score
	Params     []model.Params
}

ParamsSearchResult contains the return of grid search.

func GridSearchCV 

func GridSearchCV(estimator FactorizationMachine, trainSet *Dataset, testSet *Dataset, paramGrid model.ParamsGrid,
	_ int64, fitConfig *FitConfig, runner model.Runner) ParamsSearchResult

GridSearchCV finds the best parameters for a model.

func RandomSearchCV 

func RandomSearchCV(estimator FactorizationMachine, trainSet *Dataset, testSet *Dataset, paramGrid model.ParamsGrid,
	numTrials int, seed int64, fitConfig *FitConfig, runner model.Runner) ParamsSearchResult

RandomSearchCV searches hyper-parameters by random.

type Score 

type Score struct {
	Task      FMTask
	RMSE      float32
	Precision float32
	Recall    float32
	Accuracy  float32
	AUC       float32
}

func EvaluateClassification 

func EvaluateClassification(estimator FactorizationMachine, testSet *Dataset) Score

EvaluateClassification evaluates factorization machines in classification task.

func EvaluateRegression 

func EvaluateRegression(estimator FactorizationMachine, testSet *Dataset) Score

EvaluateRegression evaluates factorization machines in regression task.

func (Score) BetterThan 

func (score Score) BetterThan(s Score) bool

func (Score) GetValue 

func (score Score) GetValue() float32

func (Score) ZapFields added in v0.2.5 

func (score Score) ZapFields() []zap.Field

type SnapshotManger 

type SnapshotManger struct {
	BestWeights []interface{}
	BestScore   Score
}

SnapshotManger manages the best snapshot.

func (*SnapshotManger) AddSnapshot 

func (sm *SnapshotManger) AddSnapshot(score Score, weights ...interface{})

AddSnapshot adds a copied snapshot.

type UnifiedDirectIndex 

type UnifiedDirectIndex struct {
	N int32
}

UnifiedDirectIndex maps string to integer in literal.

func (*UnifiedDirectIndex) CountContextLabels 

func (unified *UnifiedDirectIndex) CountContextLabels() int32

CountContextLabels should be used by unit testing only.

func (*UnifiedDirectIndex) CountItemLabels 

func (unified *UnifiedDirectIndex) CountItemLabels() int32

CountItemLabels should be used by unit testing only.

func (*UnifiedDirectIndex) CountItems 

func (unified *UnifiedDirectIndex) CountItems() int32

CountItems should be used by unit testing only.

func (*UnifiedDirectIndex) CountUserLabels 

func (unified *UnifiedDirectIndex) CountUserLabels() int32

CountUserLabels should be used by unit testing only.

func (*UnifiedDirectIndex) CountUsers 

func (unified *UnifiedDirectIndex) CountUsers() int32

CountUsers should be used by unit testing only.

func (*UnifiedDirectIndex) EncodeContextLabel 

func (unified *UnifiedDirectIndex) EncodeContextLabel(label string) int32

EncodeContextLabel should be used by unit testing only.

func (*UnifiedDirectIndex) EncodeItem 

func (unified *UnifiedDirectIndex) EncodeItem(itemId string) int32

EncodeItem should be used by unit testing only.

func (*UnifiedDirectIndex) EncodeItemLabel 

func (unified *UnifiedDirectIndex) EncodeItemLabel(itemLabel string) int32

EncodeItemLabel should be used by unit testing only.

func (*UnifiedDirectIndex) EncodeUser 

func (unified *UnifiedDirectIndex) EncodeUser(userId string) int32

EncodeUser should be used by unit testing only.

func (*UnifiedDirectIndex) EncodeUserLabel 

func (unified *UnifiedDirectIndex) EncodeUserLabel(userLabel string) int32

EncodeUserLabel should be used by unit testing only.

func (*UnifiedDirectIndex) GetContextLabels 

func (unified *UnifiedDirectIndex) GetContextLabels() []string

GetContextLabels should be used by unit testing only.

func (*UnifiedDirectIndex) GetItemLabels 

func (unified *UnifiedDirectIndex) GetItemLabels() []string

GetItemLabels should be used by unit testing only.

func (*UnifiedDirectIndex) GetItems 

func (unified *UnifiedDirectIndex) GetItems() []string

GetItems should be used by unit testing only.

func (*UnifiedDirectIndex) GetUserLabels 

func (unified *UnifiedDirectIndex) GetUserLabels() []string

GetUserLabels should be used by unit testing only.

func (*UnifiedDirectIndex) GetUsers 

func (unified *UnifiedDirectIndex) GetUsers() []string

GetUsers should be used by unit testing only.

func (*UnifiedDirectIndex) Len 

func (unified *UnifiedDirectIndex) Len() int32

Len should be used by unit testing only.

type UnifiedIndex 

type UnifiedIndex interface {
	Len() int32
	EncodeUser(userId string) int32
	EncodeItem(itemId string) int32
	EncodeUserLabel(userLabel string) int32
	EncodeItemLabel(itemLabel string) int32
	EncodeContextLabel(ctxLabel string) int32
	GetUsers() []string
	GetItems() []string
	GetUserLabels() []string
	GetItemLabels() []string
	GetContextLabels() []string
	CountUsers() int32
	CountItems() int32
	CountUserLabels() int32
	CountItemLabels() int32
	CountContextLabels() int32
}

UnifiedIndex maps users, items and labels into a unified encoding space.

func NewUnifiedDirectIndex 

func NewUnifiedDirectIndex(n int32) UnifiedIndex

NewUnifiedDirectIndex creates a UnifiedDirectIndex.

type UnifiedMapIndex 

type UnifiedMapIndex struct {
	UserIndex      base.Index
	ItemIndex      base.Index
	UserLabelIndex base.Index
	ItemLabelIndex base.Index
	CtxLabelIndex  base.Index
}

UnifiedMapIndex is the id -> index mapper for factorization machines. The division of id is: | user | item | user label | item label | context label |

func (*UnifiedMapIndex) CountContextLabels 

func (unified *UnifiedMapIndex) CountContextLabels() int32

CountContextLabels returns the number of context labels.

func (*UnifiedMapIndex) CountItemLabels 

func (unified *UnifiedMapIndex) CountItemLabels() int32

CountItemLabels returns the number of item labels.

func (*UnifiedMapIndex) CountItems 

func (unified *UnifiedMapIndex) CountItems() int32

CountItems returns the number of items.

func (*UnifiedMapIndex) CountUserLabels 

func (unified *UnifiedMapIndex) CountUserLabels() int32

CountUserLabels returns the number of user labels.

func (*UnifiedMapIndex) CountUsers 

func (unified *UnifiedMapIndex) CountUsers() int32

CountUsers returns the number of users.

func (*UnifiedMapIndex) EncodeContextLabel 

func (unified *UnifiedMapIndex) EncodeContextLabel(label string) int32

EncodeContextLabel converts a context label to a integer in the encoding space.

func (*UnifiedMapIndex) EncodeItem 

func (unified *UnifiedMapIndex) EncodeItem(itemId string) int32

EncodeItem converts a item id to a integer in the encoding space.

func (*UnifiedMapIndex) EncodeItemLabel 

func (unified *UnifiedMapIndex) EncodeItemLabel(itemLabel string) int32

EncodeItemLabel converts a item label to a integer in the encoding space.

func (*UnifiedMapIndex) EncodeUser 

func (unified *UnifiedMapIndex) EncodeUser(userId string) int32

EncodeUser converts a user id to a integer in the encoding space.

func (*UnifiedMapIndex) EncodeUserLabel 

func (unified *UnifiedMapIndex) EncodeUserLabel(userLabel string) int32

EncodeUserLabel converts a user label to a integer in the encoding space.

func (*UnifiedMapIndex) GetContextLabels 

func (unified *UnifiedMapIndex) GetContextLabels() []string

GetContextLabels returns all context labels.

func (*UnifiedMapIndex) GetItemLabels 

func (unified *UnifiedMapIndex) GetItemLabels() []string

GetItemLabels returns all item labels.

func (*UnifiedMapIndex) GetItems 

func (unified *UnifiedMapIndex) GetItems() []string

GetItems returns all items.

func (*UnifiedMapIndex) GetUserLabels 

func (unified *UnifiedMapIndex) GetUserLabels() []string

GetUserLabels returns all user labels.

func (*UnifiedMapIndex) GetUsers 

func (unified *UnifiedMapIndex) GetUsers() []string

GetUsers returns all users.

func (*UnifiedMapIndex) Len 

func (unified *UnifiedMapIndex) Len() int32

Len returns the size of unified index.

type UnifiedMapIndexBuilder 

type UnifiedMapIndexBuilder struct {
	UserIndex      base.Index
	ItemIndex      base.Index
	UserLabelIndex base.Index
	ItemLabelIndex base.Index
	CtxLabelIndex  base.Index
}

UnifiedMapIndexBuilder is the builder for UnifiedMapIndex.

func NewUnifiedMapIndexBuilder 

func NewUnifiedMapIndexBuilder() *UnifiedMapIndexBuilder

NewUnifiedMapIndexBuilder creates a UnifiedMapIndexBuilder.

func (*UnifiedMapIndexBuilder) AddCtxLabel 

func (builder *UnifiedMapIndexBuilder) AddCtxLabel(ctxLabel string)

AddCtxLabel adds a context label the unified index.

func (*UnifiedMapIndexBuilder) AddItem 

func (builder *UnifiedMapIndexBuilder) AddItem(itemId string)

AddItem adds a item into the unified index.

func (*UnifiedMapIndexBuilder) AddItemLabel 

func (builder *UnifiedMapIndexBuilder) AddItemLabel(itemLabel string)

AddItemLabel adds a item label into the unified index.

func (*UnifiedMapIndexBuilder) AddUser 

func (builder *UnifiedMapIndexBuilder) AddUser(userId string)

AddUser adds a user into the unified index.

func (*UnifiedMapIndexBuilder) AddUserLabel 

func (builder *UnifiedMapIndexBuilder) AddUserLabel(userLabel string)

AddUserLabel adds a user label into the unified index.

func (*UnifiedMapIndexBuilder) Build 

func (builder *UnifiedMapIndexBuilder) Build() UnifiedIndex

Build UnifiedMapIndex from UnifiedMapIndexBuilder.

Source Files

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