Data Mining Extensions - DMX - Reference

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Bike Buyer Bike Buyer = Yes Bike Buyer = No 1 0.867074195848097 0.132755556974282 See Also Data Mining Functions Reference) Functions (DMX) Mapping Functions to Query Types (DMX) PredictSequence Predicts future sequence values for a specified set of sequence data. Syntax PredictSequence() PredictSequence() PredictSequence() Return Type A . Remarks If the n parameter is specified, it returns the following values: • If n is greater than zero, the most likely sequence values in the next n steps. • If both n-start and n-end are specified, the sequence values from n-start to n-end. Examples The following example returns a sequence of the five products that are most likely to be purchased by a customer in the Adventure Works DW Multidimensional 2012 database based on the Sequence Clustering mining model. SELECT PredictSequence([Sequence Clustering].[v Assoc Seq Line Items],5) From [Sequence Clustering] See Also Mapping Functions to Query Types (DMX) Functions (DMX) Mapping Functions to Query Types (DMX) 121
PredictStdev Returns the predicted standard deviation for the specified column. Syntax PredictStdev() Applies To A scalar column. Return Type A scalar value of the type that is specified by . Remarks If the column reference is discrete, PredictStdev returns 0 because the standard deviation cannot be calculated from discrete values. Examples The following example uses a natural prediction join to determine whether an individual is likely to be a bike buyer based on the TM Decision Tree mining model, and also determines the standard deviation for the prediction. SELECT [Bike Buyer], PredictStdev([Bike Buyer]) AS [Standard Deviation] FROM [TM Decision Tree] NATURAL PREDICTION JOIN (SELECT 28 AS [Age], '2-5 Miles' AS [Commute Distance], 'Graduate Degree' AS [Education], 0 AS [Number Cars Owned], 0 AS [Number Children At Home]) AS t See Also Mapping Functions to Query Types (DMX) Functions (DMX) Mapping Functions to Query Types (DMX) 122
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Data Mining Extensions (DMX) Refere
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Contents Data Mining Extensions (DM
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* (Multiply) ......................
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• Create a mining structure by us
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The type of query you use depends o
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Each of these tasks uses a differen
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Back to Select Types Drillthrough Y
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Query type Supported functions Rema
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Query type Supported functions Rema
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An object identifier is created whe
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Data types depend on the algorithm.
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You can use operators to combine sm
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Operator Description argument on th
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Understanding the Select Statement
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DMX Syntax Conventions DMX Syntax E
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DMX Syntax Elements Understanding t
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Columns that are left unspecified i
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Data Mining Extensions (DMX) Statem
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Statement DROP MINING MODEL (DMX) D
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• Relationship to an attribute co
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) Example 2: Specifying Holdout Per
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parameter list Optional. A comma-se
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Filter Criteria Expressions You can
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[Model] = 'ML Road Tire' ) ) ) WITH
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For a list of the data types, conte
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[Model] TEXT DISCRETE PREDICT ) ) U
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object name Optional. The name of t
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parameter list Optional. A comma-se
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Arguments model A model identifier.
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If you use INSERT INTO with a minin
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) SHAPE { OPENQUERY([AdventureWorks
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• SELECT FROM PREDICTION JOIN •
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Example results: Gender F M For col
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SELECT FROM .CONTENT Returns the mi
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Examples The following code returns
Page 72 and 73: DMX Data Manipulation Statements DM
Page 74 and 75: Not all mining model types support
Page 76 and 77: Remarks Algorithm providers define
Page 78 and 79: query to columns in the mining mode
Page 80 and 81: [HouseOwnerFlag], [NumberCarsOwned]
Page 82 and 83: expression list n A comma-separated
Page 84 and 85: Example 1: Drill through to Structu
Page 86 and 87: query syntax A query syntax that re
Page 88 and 89: ... RELATE TO ) AS < column table
Page 90 and 91: esults of the prediction are return
Page 92 and 93: Function RangeMax RangeMid RangeMin
Page 94 and 95: Model $SUPPORT $PROBABILITY $ADJUST
Page 96 and 97: A column in the nested table, or ex
Page 98 and 99: example uses $SUPPORT because suppo
Page 102 and 103: Examples The following example uses
Page 104 and 105: 'Graduate Degree' AS [Education], 0
Page 106 and 107: For more information about using th
Page 108 and 109: A Boolean type. Remarks IsDescendan
Page 110 and 111: Functions (DMX) Querying Data Minin
Page 112 and 113: Predict(, [option1], [option2], [op
Page 114 and 115: Syntax PredictAdjustedProbability(,
Page 116 and 117: See Also Mapping Functions to Query
Page 118 and 119: PredictHistogram( | ) Applies To A
Page 120 and 121: Return Type Examples The following
Page 124 and 125: PredictSupport Returns the support
Page 126 and 127: n-start, n-end Specifies a range of
Page 128 and 129: this query returns two columns. The
Page 130 and 131: WHERE ([Model Region] = 'M200 Europ
Page 132 and 133: Model Region Europe M200 Europe M20
Page 134 and 135: Scalar columns. Return Type A scala
Page 136 and 137: Scalar columns. Return Type A scala
Page 138 and 139: We will use the following mining st
Page 140 and 141: product name, but also returns the
Page 144 and 145: Applies To An expression that retur
Page 146 and 147: The third argument to the TopPercen
Page 150 and 151: Operator Description argument or bo
Page 152 and 153: + (Add) Performs an arithmetic oper
Page 154 and 155: Operators (DMX) Data Mining Extensi
Page 156 and 157: Return Value A Boolean value that c
Page 158 and 159: Return Value A Boolean value that c
Page 160 and 161: NOT A logical operator that perform
Page 162 and 163: Syntax + Numeric_Expression Paramet
Page 164 and 165: -- Comment_Text Parameters Paramete
Page 166 and 167: Convention Usage syntax that can be
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Data Mining Extensions - DMX - Reference

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