Class: LogisticRegressionModel

eclairjs/ml/classification. LogisticRegressionModel

Model produced by module:eclairjs/ml/classification.LogisticRegression.

Constructor

new LogisticRegressionModel()

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Extends

Methods

(static) load(path) → {module:eclairjs/mllib/classification.LogisticRegressionModel}

Parameters:
Name Type Description
path string
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Returns:
Type
module:eclairjs/mllib/classification.LogisticRegressionModel

(static) read() → {module:eclairjs/ml/util.MLReader}

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Returns:
Type
module:eclairjs/ml/util.MLReader

coefficients() → {module:eclairjs/mllib/linalg.Vector}

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Returns:
Type
module:eclairjs/mllib/linalg.Vector

copy(extra) → {module:eclairjs/mllib/classification.LogisticRegressionModel}

Parameters:
Name Type Description
extra module:eclairjs/ml/param.ParamMap
Overrides:
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Returns:
Type
module:eclairjs/mllib/classification.LogisticRegressionModel

evaluate(dataset) → {module:eclairjs/ml/classification.LogisticRegressionSummary}

Evaluates the model on a test dataset.
Parameters:
Name Type Description
dataset module:eclairjs/sql.Dataset Test dataset to evaluate model on.
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Returns:
Type
module:eclairjs/ml/classification.LogisticRegressionSummary

featuresCol() → {module:eclairjs/ml/param.Param}

Param for features column name.
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Returns:
Type
module:eclairjs/ml/param.Param

getFeaturesCol() → {string}

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Returns:
Type
string

getLabelCol() → {string}

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Returns:
Type
string

getPredictionCol() → {string}

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Returns:
Type
string

getThreshold() → {float}

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Returns:
Type
float

getThresholds() → {Array.<float>}

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Returns:
Type
Array.<float>

hasParent() → {boolean}

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Returns:
Type
boolean

hasSummary() → {boolean}

Indicates whether a training summary exists for this model instance.
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Returns:
Type
boolean

intercept() → {float}

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Returns:
Type
float

labelCol() → {module:eclairjs/ml/param.Param}

Param for label column name.
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Returns:
Type
module:eclairjs/ml/param.Param

numClasses() → {int}

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Returns:
Type
int

numFeatures() → {integer}

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Returns:
Type
integer

parent() → {module:eclairjs/ml.Estimator}

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Returns:
Type
module:eclairjs/ml.Estimator

predictionCol() → {module:eclairjs/ml/param.Param}

Param for prediction column name.
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Returns:
Type
module:eclairjs/ml/param.Param

setFeaturesCol(value) → {object}

Parameters:
Name Type Description
value string
Inherited From:
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Returns:
Type
object

setParent(parent) → {object}

Sets the parent of this model.
Parameters:
Name Type Description
parent module:eclairjs/ml.Estimator
Inherited From:
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Returns:
Type
object

setPredictionCol(value) → {object}

Parameters:
Name Type Description
value string
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Returns:
Type
object

setProbabilityCol(value) → {module:eclairjs/ml/classification.ProbabilisticClassificationModel}

Parameters:
Name Type Description
value string
Inherited From:
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Returns:
Type
module:eclairjs/ml/classification.ProbabilisticClassificationModel

setRawPredictionCol(value) → {module:eclairjs/ml/classification.ClassificationModel}

Parameters:
Name Type Description
value string
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Returns:
Type
module:eclairjs/ml/classification.ClassificationModel

setThreshold(value) → {module:eclairjs/mllib/classification.LogisticRegressionModel}

Parameters:
Name Type Description
value float
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Returns:
Type
module:eclairjs/mllib/classification.LogisticRegressionModel

setThresholds(value) → {module:eclairjs/mllib/classification.LogisticRegressionModel}

Parameters:
Name Type Description
value Array.<float>
Overrides:
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Returns:
Type
module:eclairjs/mllib/classification.LogisticRegressionModel

summary() → {module:eclairjs/ml/classification.LogisticRegressionTrainingSummary}

Gets summary of model on training set. An exception is thrown if `trainingSummary == None`.
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Returns:
Type
module:eclairjs/ml/classification.LogisticRegressionTrainingSummary

transform(dataset) → {module:eclairjs/sql.Dataset}

Transforms dataset by reading from featuresCol, and appending new columns as specified by parameters: - predicted labels as [[predictionCol]] of type Double - raw predictions (confidences) as [[rawPredictionCol]] of type Vector - probability of each class as [[probabilityCol]] of type Vector.
Parameters:
Name Type Description
dataset module:eclairjs/sql.Dataset input dataset
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Returns:
transformed dataset
Type
module:eclairjs/sql.Dataset

transformSchema(schema) → {module:eclairjs/sql/types.StructType}

Parameters:
Name Type Description
schema module:eclairjs/sql/types.StructType
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Returns:
Type
module:eclairjs/sql/types.StructType

uid() → {string}

An immutable unique ID for the object and its derivatives.
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Returns:
Type
string

validateAndTransformSchema(schema, fitting, featuresDataType) → {module:eclairjs/sql/types.StructType}

Validates and transforms the input schema with the provided param map.
Parameters:
Name Type Description
schema module:eclairjs/sql/types.StructType
fitting boolean whether this is in fitting
featuresDataType module:eclairjs/sql/types.DataType SQL DataType for FeaturesType. E.g., module:eclairjs/sql/types.VectorUDTfor vector features
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Returns:
Type
module:eclairjs/sql/types.StructType

write() → {module:eclairjs/ml/util.MLWriter}

Returns a MLWriter instance for this ML instance. For [[LogisticRegressionModel]], this does NOT currently save the training summary. An option to save summary may be added in the future. This also does not save the parent currently.
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Returns:
Type
module:eclairjs/ml/util.MLWriter