Why Go
- Case Studies
  
  Common problems companies solve with Go
- Use Cases
  
  Stories about how and why companies use Go
- Security Policy
  
  How Go can help keep you secure by default
Learn
Docs
- Effective Go
  
  Tips for writing clear, performant, and idiomatic Go code
- Go User Manual
  
  A complete introduction to building software with Go
- Standard library
  
  Reference documentation for Go's standard library
- Release Notes
  
  Learn what's new in each Go release
Packages
Community
- Recorded Talks
  
  Videos from prior events
- Meetups
  
  Meet other local Go developers
- Conferences
  
  Learn and network with Go developers from around the world
- Go blog
  
  The Go project's official blog.
- Go project
  
  Get help and stay informed from Go
- Get connected

core

package

Go to main page

Versions in this module

v0

v0.1.3

Dec 21, 2019

Changes in this version

+ func Popularity(dataSet DataSetInterface) (itemId []string, popularity []float64)

v0.1.2

Dec 14, 2019

v0.1.1

Nov 24, 2019

Changes in this version

+ var DataSetDir string

+ var GorseDir string

+ var TempDir string

+ func Copy(dst, src interface{}) error

+ func EvaluateAUC(estimator ModelInterface, testSet, excludeSet DataSetInterface) float64

+ func EvaluateRank(estimator ModelInterface, testSet DataSetInterface, ...) []float64

+ func EvaluateRating(estimator ModelInterface, testSet DataSetInterface, metrics ...RatingMetric) []float64

+ func Items(dataSet ...DataSetInterface) map[int]bool

+ func LoadEntityFromCSV(filePath string, fieldSep string, tagSep string, header bool, names []string, ...) []map[string]interface

+ func MAE(groundTruth []float64, prediction []float64) float64

+ func MAP(targetSet *base.MarginalSubSet, rankList []int) float64

+ func MRR(targetSet *base.MarginalSubSet, rankList []int) float64

+ func NDCG(targetSet *base.MarginalSubSet, rankList []int) float64

+ func Neighbors(dataSet DataSetInterface, itemId int, n int, similarity base.FuncSimilarity) ([]int, []float64)

+ func Popular(dataSet DataSetInterface, n int) ([]int, []float64)

+ func Precision(targetSet *base.MarginalSubSet, rankList []int) float64

+ func RMSE(groundTruth []float64, prediction []float64) float64

+ func Recall(targetSet *base.MarginalSubSet, rankList []int) float64

+ func Top(items map[int]bool, userId int, n int, exclude *base.MarginalSubSet, ...) ([]int, []float64)

+ type CrossValidateResult struct

+ TestCosts []float64

+ TestScore []float64

+ func CrossValidate(model ModelInterface, dataSet DataSetInterface, splitter Splitter, seed int64, ...) []CrossValidateResult

+ func (sv CrossValidateResult) MeanAndMargin() (float64, float64)

+ type CrossValidationEvaluator func(estimator ModelInterface, testSet, trainSet DataSetInterface) (scores, costs []float64)

+ func NewRankEvaluator(n int, metrics ...RankMetric) CrossValidationEvaluator

+ func NewRatingEvaluator(metrics ...RatingMetric) CrossValidationEvaluator

+ type DataSet struct

+ func LoadDataFromBuiltIn(dataSetName string) *DataSet

+ func LoadDataFromCSV(fileName string, sep string, hasHeader bool) *DataSet

+ func LoadDataFromNetflix(fileName string, _ string, _ bool) *DataSet

+ func NewDataSet(userIDs, itemIDs []int, ratings []float64) *DataSet

+ func (set *DataSet) Count() int

+ func (set *DataSet) FeatureCount() int

+ func (set *DataSet) Get(i int) (int, int, float64)

+ func (set *DataSet) GetWithIndex(i int) (int, int, float64)

+ func (set *DataSet) GlobalMean() float64

+ func (set *DataSet) Item(itemId int) *base.MarginalSubSet

+ func (set *DataSet) ItemByIndex(itemIndex int) *base.MarginalSubSet

+ func (set *DataSet) ItemCount() int

+ func (set *DataSet) ItemFeatures() []*base.SparseVector

+ func (set *DataSet) ItemIndexer() *base.Indexer

+ func (set *DataSet) Items() []*base.MarginalSubSet

+ func (set *DataSet) SetItemFeature(items []map[string]interface{}, features []string, idName string)

+ func (set *DataSet) SetUserFeatures(users []map[string]interface{}, features []string, idName string)

+ func (set *DataSet) SubSet(subset []int) DataSetInterface

+ func (set *DataSet) User(userId int) *base.MarginalSubSet

+ func (set *DataSet) UserByIndex(userIndex int) *base.MarginalSubSet

+ func (set *DataSet) UserCount() int

+ func (set *DataSet) UserFeatures() []*base.SparseVector

+ func (set *DataSet) UserIndexer() *base.Indexer

+ func (set *DataSet) Users() []*base.MarginalSubSet

+ type DataSetInterface interface

+ Count func() int

+ FeatureCount func() int

+ Get func(i int) (int, int, float64)

+ GetWithIndex func(i int) (int, int, float64)

+ GlobalMean func() float64

+ Item func(itemId int) *base.MarginalSubSet

+ ItemByIndex func(itemIndex int) *base.MarginalSubSet

+ ItemCount func() int

+ ItemFeatures func() []*base.SparseVector

+ ItemIndexer func() *base.Indexer

+ Items func() []*base.MarginalSubSet

+ SubSet func(subset []int) DataSetInterface

+ User func(userId int) *base.MarginalSubSet

+ UserByIndex func(userIndex int) *base.MarginalSubSet

+ UserCount func() int

+ UserFeatures func() []*base.SparseVector

+ UserIndexer func() *base.Indexer

+ Users func() []*base.MarginalSubSet

+ func NewSubSet(dataSet *DataSet, subset []int) DataSetInterface

+ func Split(data DataSetInterface, testRatio float64) (train, test DataSetInterface)

+ type ModelInterface interface

+ Fit func(trainSet DataSetInterface, options *base.RuntimeOptions)

+ GetParams func() base.Params

+ Predict func(userId, itemId int) float64

+ SetParams func(params base.Params)

+ type ModelSelectionResult struct

+ AllParams []base.Params

+ BestCost float64

+ BestIndex int

+ BestParams base.Params

+ BestScore float64

+ CVResults []CrossValidateResult

+ func GridSearchCV(estimator ModelInterface, dataSet DataSetInterface, paramGrid ParameterGrid, ...) []ModelSelectionResult

+ func RandomSearchCV(estimator ModelInterface, dataSet DataSetInterface, paramGrid ParameterGrid, ...) []ModelSelectionResult

+ type ParameterGrid map[base.ParamName][]interface

+ type RankMetric func(targetSet *base.MarginalSubSet, rankList []int) float64

+ type RatingMetric func(groundTruth []float64, prediction []float64) float64

+ type Splitter func(set DataSetInterface, seed int64) ([]DataSetInterface, []DataSetInterface)

+ func NewKFoldSplitter(k int) Splitter

+ func NewRatioSplitter(repeat int, testRatio float64) Splitter

+ func NewUserLOOSplitter(repeat int) Splitter

+ type SubSet struct

+ func (set *SubSet) Count() int

+ func (set *SubSet) Get(i int) (int, int, float64)

+ func (set *SubSet) GetWithIndex(i int) (int, int, float64)

+ func (set *SubSet) GlobalMean() float64

+ func (set *SubSet) Item(itemId int) *base.MarginalSubSet

+ func (set *SubSet) ItemByIndex(itemIndex int) *base.MarginalSubSet

+ func (set *SubSet) Items() []*base.MarginalSubSet

+ func (set *SubSet) SubSet(indices []int) DataSetInterface

+ func (set *SubSet) User(userId int) *base.MarginalSubSet

+ func (set *SubSet) UserByIndex(userIndex int) *base.MarginalSubSet

+ func (set *SubSet) Users() []*base.MarginalSubSet