Bitrix API

Base implements JsonSerializable

AbstractYes

Table of Contents

Interfaces

JsonSerializable

Methods

__construct()  : mixed
buildFeaturesVector()  : array<string|int, mixed>|false
Should return feature vector for the crm entity.
getCachedTrainingSetSize()  : array<string|int, mixed>
Cached version of getTrainingSetSize()
getCurrentTraining()  : array<string|int, mixed>
Returns current training fields
getMlModel()  : Model|null
getModelId()  : int|false
Returns id of the model.
getModelNames()  : array<string|int, string>
Should return array of available name for the model type.
getName()  : string
Return name of the model.
getPossibleFields()  : array<string|int, mixed>
Should return array of field descriptions.
getPredictionSet()  : array<string|int, mixed>
getRowIdField()  : string|false
Return name of the row id field in the feature vector.
getState()  : string|false
getTargetField()  : string|false
Return name of the target field in the feature vector.
getTitle()  : string
Should return title for this model
getTrainingSet()  : array<string|int, int>
Should return array of the ids of the entities, that should be used for building the next part of the training set
getTrainingSetSize()  : array<string|int, mixed>
Should return count of successful and failed records in the training set for this model.
hasAccess()  : bool
isReady()  : bool
Returns true if model is ready for real-time prediction.
jsonSerialize()  : array<string|int, mixed>
setMlModel()  : void
unassociateMlModel()  : void

Methods

__construct()

public __construct(string $name) : mixed
Parameters
$name : string

buildFeaturesVector()

Should return feature vector for the crm entity.

public abstract buildFeaturesVector(int $entityId) : array<string|int, mixed>|false
Parameters
$entityId : int

Id of the entity.

Return values
array<string|int, mixed>|false

getCachedTrainingSetSize()

Cached version of getTrainingSetSize()

public getCachedTrainingSetSize() : array<string|int, mixed>
Return values
array<string|int, mixed>

getCurrentTraining()

Returns current training fields

public getCurrentTraining() : array<string|int, mixed>
Tags
throws
SystemException
throws
ArgumentException
throws
ObjectPropertyException
Return values
array<string|int, mixed>

getMlModel()

public getMlModel() : Model|null
Return values
Model|null

getModelId()

Returns id of the model.

public getModelId() : int|false
Return values
int|false

getModelNames()

Should return array of available name for the model type.

public static getModelNames() : array<string|int, string>
Return values
array<string|int, string>

getName()

Return name of the model.

public getName() : string
Return values
string

getPossibleFields()

Should return array of field descriptions.

public abstract getPossibleFields() : array<string|int, mixed>
Return values
array<string|int, mixed>

getPredictionSet()

public abstract getPredictionSet(mixed $fromId, mixed $limit) : array<string|int, mixed>
Parameters
$fromId : mixed
$limit : mixed
Return values
array<string|int, mixed>

getRowIdField()

Return name of the row id field in the feature vector.

public getRowIdField() : string|false
Return values
string|false

getState()

public getState() : string|false
Return values
string|false

getTargetField()

Return name of the target field in the feature vector.

public getTargetField() : string|false
Return values
string|false

getTitle()

Should return title for this model

public abstract getTitle() : string
Return values
string

getTrainingSet()

Should return array of the ids of the entities, that should be used for building the next part of the training set

public abstract getTrainingSet(int $fromId, int $limit) : array<string|int, int>
Parameters
$fromId : int

Id of the starting entity.

$limit : int

Maximum count of the records in the training subset.

Return values
array<string|int, int>

getTrainingSetSize()

Should return count of successful and failed records in the training set for this model.

public abstract getTrainingSetSize() : array<string|int, mixed>
Return values
array<string|int, mixed>

hasAccess()

public abstract hasAccess([int $userId = 0 ]) : bool
Parameters
$userId : int = 0
Return values
bool

isReady()

Returns true if model is ready for real-time prediction.

public isReady() : bool
Return values
bool

jsonSerialize()

public jsonSerialize() : array<string|int, mixed>
Return values
array<string|int, mixed>

setMlModel()

public setMlModel(Model $mlModel) : void
Parameters
$mlModel : Model

unassociateMlModel()

public unassociateMlModel() : void 

        

        
    




    

    

                                

                

                                
    

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