mmlspark.nn package¶

Submodules¶

mmlspark.nn.ConditionalBallTree module¶

class mmlspark.nn.ConditionalBallTree.ConditionalBallTree(keys, values, labels, leafSize, java_obj=None)[source]¶

Bases: object

findMaximumInnerProducts(queryPoint, conditioner, k)[source]¶: Find the best match to the queryPoint given the conditioner and k from self. :param queryPoint: array vector to use to query for NNs :param conditioner: set of labels that will subset or condition the NN query :param k: int representing the maximum number of neighbors to return :return: array of tuples representing the index of the match and its distance

static load(filename)[source]¶

save(filename)[source]¶

mmlspark.nn.ConditionalKNN module¶

class mmlspark.nn.ConditionalKNN.ConditionalKNN(*args, **kwargs)[source]¶

Bases: mmlspark.core.schema.Utils.ComplexParamsMixin, pyspark.ml.util.JavaMLReadable, pyspark.ml.util.JavaMLWritable, pyspark.ml.wrapper.JavaEstimator

Parameters

conditionerCol (str) – column holding identifiers for features that will be returned when queried (default: conditioner)
featuresCol (str) – The name of the features column (default: features)
k (int) – number of matches to return (default: 5)
labelCol (str) – The name of the label column (default: labels)
leafSize (int) – max size of the leaves of the tree (default: 50)
outputCol (str) – The name of the output column (default: [self.uid]_output)
valuesCol (str) – column holding values for each feature (key) that will be returned when queried (default: values)

getConditionerCol()[source]¶

Returns: column holding identifiers for features that will be returned when queried (default: conditioner)
Return type: str

getFeaturesCol()[source]¶

Returns: The name of the features column (default: features)
Return type: str

static getJavaPackage()[source]¶: Returns package name String.

getK()[source]¶

Returns: number of matches to return (default: 5)
Return type: int

getLabelCol()[source]¶

Returns: The name of the label column (default: labels)
Return type: str

getLeafSize()[source]¶

Returns: max size of the leaves of the tree (default: 50)
Return type: int

getOutputCol()[source]¶

Returns: The name of the output column (default: [self.uid]_output)
Return type: str

getValuesCol()[source]¶

Returns: column holding values for each feature (key) that will be returned when queried (default: values)
Return type: str

classmethod read()[source]¶: Returns an MLReader instance for this class.

setConditionerCol(value)[source]¶

Parameters: conditionerCol – column holding identifiers for features that will be returned when queried (default: conditioner)

setFeaturesCol(value)[source]¶

Parameters: featuresCol – The name of the features column (default: features)

setK(value)[source]¶

Parameters: k – number of matches to return (default: 5)

setLabelCol(value)[source]¶

Parameters: labelCol – The name of the label column (default: labels)

setLeafSize(value)[source]¶

Parameters: leafSize – max size of the leaves of the tree (default: 50)

setOutputCol(value)[source]¶

Parameters: outputCol – The name of the output column (default: [self.uid]_output)

setParams(conditionerCol='conditioner', featuresCol='features', k=5, labelCol='labels', leafSize=50, outputCol=None, valuesCol='values')[source]¶

Set the (keyword only) parameters

Parameters

conditionerCol (str) – column holding identifiers for features that will be returned when queried (default: conditioner)
featuresCol (str) – The name of the features column (default: features)
k (int) – number of matches to return (default: 5)
labelCol (str) – The name of the label column (default: labels)
leafSize (int) – max size of the leaves of the tree (default: 50)
outputCol (str) – The name of the output column (default: [self.uid]_output)
valuesCol (str) – column holding values for each feature (key) that will be returned when queried (default: values)

setValuesCol(value)[source]¶

Parameters: valuesCol – column holding values for each feature (key) that will be returned when queried (default: values)

class mmlspark.nn.ConditionalKNN.ConditionalKNNModel(java_model=None)[source]¶

Bases: mmlspark.core.schema.Utils.ComplexParamsMixin, pyspark.ml.wrapper.JavaModel, pyspark.ml.util.JavaMLWritable, pyspark.ml.util.JavaMLReadable

Model fitted by ConditionalKNN.

getBallTree()[source]¶

Returns: the ballTree model used for perfoming queries
Return type: object

getConditionerCol()[source]¶

Returns: column holding identifiers for features that will be returned when queried
Return type: str

getFeaturesCol()[source]¶

Returns: The name of the features column
Return type: str

static getJavaPackage()[source]¶: Returns package name String.

getK()[source]¶

Returns: number of matches to return
Return type: int

getLabelCol()[source]¶

Returns: The name of the label column
Return type: str

getLeafSize()[source]¶

Returns: max size of the leaves of the tree
Return type: int

getOutputCol()[source]¶

Returns: The name of the output column
Return type: str

getValuesCol()[source]¶

Returns: column holding values for each feature (key) that will be returned when queried
Return type: str

classmethod read()[source]¶: Returns an MLReader instance for this class.

setBallTree(value)[source]¶

Parameters: ballTree – the ballTree model used for perfoming queries

setConditionerCol(value)[source]¶

Parameters: conditionerCol – column holding identifiers for features that will be returned when queried

setFeaturesCol(value)[source]¶

Parameters: featuresCol – The name of the features column

setK(value)[source]¶

Parameters: k – number of matches to return

setLabelCol(value)[source]¶

Parameters: labelCol – The name of the label column

setLeafSize(value)[source]¶

Parameters: leafSize – max size of the leaves of the tree

setOutputCol(value)[source]¶

Parameters: outputCol – The name of the output column

setValuesCol(value)[source]¶

Parameters: valuesCol – column holding values for each feature (key) that will be returned when queried

mmlspark.nn.ConditionalKNNModel module¶

class mmlspark.nn.ConditionalKNNModel.ConditionalKNNModel(*args, **kwargs)[source]¶

Bases: mmlspark.core.schema.Utils.ComplexParamsMixin, pyspark.ml.util.JavaMLReadable, pyspark.ml.util.JavaMLWritable, pyspark.ml.wrapper.JavaTransformer

Parameters

ballTree (object) – the ballTree model used for perfoming queries
conditionerCol (str) – column holding identifiers for features that will be returned when queried
featuresCol (str) – The name of the features column
k (int) – number of matches to return
labelCol (str) – The name of the label column
leafSize (int) – max size of the leaves of the tree
outputCol (str) – The name of the output column
valuesCol (str) – column holding values for each feature (key) that will be returned when queried

getBallTree()[source]¶

Returns: the ballTree model used for perfoming queries
Return type: object

getConditionerCol()[source]¶

Returns: column holding identifiers for features that will be returned when queried
Return type: str

getFeaturesCol()[source]¶

Returns: The name of the features column
Return type: str

static getJavaPackage()[source]¶: Returns package name String.

getK()[source]¶

Returns: number of matches to return
Return type: int

getLabelCol()[source]¶

Returns: The name of the label column
Return type: str

getLeafSize()[source]¶

Returns: max size of the leaves of the tree
Return type: int

getOutputCol()[source]¶

Returns: The name of the output column
Return type: str

getValuesCol()[source]¶

Returns: column holding values for each feature (key) that will be returned when queried
Return type: str

classmethod read()[source]¶: Returns an MLReader instance for this class.

setBallTree(value)[source]¶

Parameters: ballTree – the ballTree model used for perfoming queries

setConditionerCol(value)[source]¶

Parameters: conditionerCol – column holding identifiers for features that will be returned when queried

setFeaturesCol(value)[source]¶

Parameters: featuresCol – The name of the features column

setK(value)[source]¶

Parameters: k – number of matches to return

setLabelCol(value)[source]¶

Parameters: labelCol – The name of the label column

setLeafSize(value)[source]¶

Parameters: leafSize – max size of the leaves of the tree

setOutputCol(value)[source]¶

Parameters: outputCol – The name of the output column

setParams(ballTree=None, conditionerCol=None, featuresCol=None, k=None, labelCol=None, leafSize=None, outputCol=None, valuesCol=None)[source]¶

Set the (keyword only) parameters

Parameters

ballTree (object) – the ballTree model used for perfoming queries
conditionerCol (str) – column holding identifiers for features that will be returned when queried
featuresCol (str) – The name of the features column
k (int) – number of matches to return
labelCol (str) – The name of the label column
leafSize (int) – max size of the leaves of the tree
outputCol (str) – The name of the output column
valuesCol (str) – column holding values for each feature (key) that will be returned when queried

setValuesCol(value)[source]¶

Parameters: valuesCol – column holding values for each feature (key) that will be returned when queried

mmlspark.nn.KNN module¶

class mmlspark.nn.KNN.KNN(*args, **kwargs)[source]¶

Bases: mmlspark.core.schema.Utils.ComplexParamsMixin, pyspark.ml.util.JavaMLReadable, pyspark.ml.util.JavaMLWritable, pyspark.ml.wrapper.JavaEstimator

Parameters

featuresCol (str) – The name of the features column (default: features)
k (int) – number of matches to return (default: 5)
leafSize (int) – max size of the leaves of the tree (default: 50)
outputCol (str) – The name of the output column (default: [self.uid]_output)
valuesCol (str) – column holding values for each feature (key) that will be returned when queried (default: values)

getFeaturesCol()[source]¶

Returns: The name of the features column (default: features)
Return type: str

static getJavaPackage()[source]¶: Returns package name String.

getK()[source]¶

Returns: number of matches to return (default: 5)
Return type: int

getLeafSize()[source]¶

Returns: max size of the leaves of the tree (default: 50)
Return type: int

getOutputCol()[source]¶

Returns: The name of the output column (default: [self.uid]_output)
Return type: str

getValuesCol()[source]¶

Returns: column holding values for each feature (key) that will be returned when queried (default: values)
Return type: str

classmethod read()[source]¶: Returns an MLReader instance for this class.

setFeaturesCol(value)[source]¶

Parameters: featuresCol – The name of the features column (default: features)

setK(value)[source]¶

Parameters: k – number of matches to return (default: 5)

setLeafSize(value)[source]¶

Parameters: leafSize – max size of the leaves of the tree (default: 50)

setOutputCol(value)[source]¶

Parameters: outputCol – The name of the output column (default: [self.uid]_output)

setParams(featuresCol='features', k=5, leafSize=50, outputCol=None, valuesCol='values')[source]¶

Set the (keyword only) parameters

Parameters

featuresCol (str) – The name of the features column (default: features)
k (int) – number of matches to return (default: 5)
leafSize (int) – max size of the leaves of the tree (default: 50)
outputCol (str) – The name of the output column (default: [self.uid]_output)
valuesCol (str) – column holding values for each feature (key) that will be returned when queried (default: values)

setValuesCol(value)[source]¶

Parameters: valuesCol – column holding values for each feature (key) that will be returned when queried (default: values)

class mmlspark.nn.KNN.KNNModel(java_model=None)[source]¶

Bases: mmlspark.core.schema.Utils.ComplexParamsMixin, pyspark.ml.wrapper.JavaModel, pyspark.ml.util.JavaMLWritable, pyspark.ml.util.JavaMLReadable

Model fitted by KNN.

getBallTree()[source]¶

Returns: the ballTree model used for perfoming queries
Return type: object

getFeaturesCol()[source]¶

Returns: The name of the features column
Return type: str

static getJavaPackage()[source]¶: Returns package name String.

getK()[source]¶

Returns: number of matches to return
Return type: int

getLeafSize()[source]¶

Returns: max size of the leaves of the tree
Return type: int

getOutputCol()[source]¶

Returns: The name of the output column
Return type: str

getValuesCol()[source]¶

Returns: column holding values for each feature (key) that will be returned when queried
Return type: str

classmethod read()[source]¶: Returns an MLReader instance for this class.

setBallTree(value)[source]¶

Parameters: ballTree – the ballTree model used for perfoming queries

setFeaturesCol(value)[source]¶

Parameters: featuresCol – The name of the features column

setK(value)[source]¶

Parameters: k – number of matches to return

setLeafSize(value)[source]¶

Parameters: leafSize – max size of the leaves of the tree

setOutputCol(value)[source]¶

Parameters: outputCol – The name of the output column

setValuesCol(value)[source]¶

Parameters: valuesCol – column holding values for each feature (key) that will be returned when queried

mmlspark.nn.KNNModel module¶

class mmlspark.nn.KNNModel.KNNModel(*args, **kwargs)[source]¶

Bases: mmlspark.core.schema.Utils.ComplexParamsMixin, pyspark.ml.util.JavaMLReadable, pyspark.ml.util.JavaMLWritable, pyspark.ml.wrapper.JavaTransformer

Parameters

ballTree (object) – the ballTree model used for perfoming queries
featuresCol (str) – The name of the features column
k (int) – number of matches to return
leafSize (int) – max size of the leaves of the tree
outputCol (str) – The name of the output column
valuesCol (str) – column holding values for each feature (key) that will be returned when queried

getBallTree()[source]¶

Returns: the ballTree model used for perfoming queries
Return type: object

getFeaturesCol()[source]¶

Returns: The name of the features column
Return type: str

static getJavaPackage()[source]¶: Returns package name String.

getK()[source]¶

Returns: number of matches to return
Return type: int

getLeafSize()[source]¶

Returns: max size of the leaves of the tree
Return type: int

getOutputCol()[source]¶

Returns: The name of the output column
Return type: str

getValuesCol()[source]¶

Returns: column holding values for each feature (key) that will be returned when queried
Return type: str

classmethod read()[source]¶: Returns an MLReader instance for this class.

setBallTree(value)[source]¶

Parameters: ballTree – the ballTree model used for perfoming queries

setFeaturesCol(value)[source]¶

Parameters: featuresCol – The name of the features column

setK(value)[source]¶

Parameters: k – number of matches to return

setLeafSize(value)[source]¶

Parameters: leafSize – max size of the leaves of the tree

setOutputCol(value)[source]¶

Parameters: outputCol – The name of the output column

setParams(ballTree=None, featuresCol=None, k=None, leafSize=None, outputCol=None, valuesCol=None)[source]¶

Set the (keyword only) parameters

Parameters

ballTree (object) – the ballTree model used for perfoming queries
featuresCol (str) – The name of the features column
k (int) – number of matches to return
leafSize (int) – max size of the leaves of the tree
outputCol (str) – The name of the output column
valuesCol (str) – column holding values for each feature (key) that will be returned when queried

setValuesCol(value)[source]¶

Parameters: valuesCol – column holding values for each feature (key) that will be returned when queried

Module contents¶

MicrosoftML is a library of Python classes to interface with the Microsoft scala APIs to utilize Apache Spark to create distibuted machine learning models.

MicrosoftML simplifies training and scoring classifiers and regressors, as well as facilitating the creation of models using the CNTK library, images, and text.