public class StatsFunctions extends Object
Modifier and Type | Class and Description |
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static class |
StatsFunctions.NormalizeMethod
Supported methods of value normalization.
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Modifier and Type | Method and Description |
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static ScalarValuedFunction |
minmax(ScalarValuedFunction expr,
BigDecimal min,
BigDecimal max)
Create a MinMax normalization function for the given subexpression.
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static ScalarValuedFunction |
minmax(ScalarValuedFunction expr,
double min,
double max)
Create a MinMax normalization function for the given subexpression.
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static ScalarValuedFunction |
minmax(String field,
BigDecimal min,
BigDecimal max)
Create a MinMax normalization function for the input field.
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static ScalarValuedFunction |
minmax(String field,
double min,
double max)
Create a MinMax normalization function for the input field.
|
static ScalarValuedFunction |
normalizeFunction(StatsFunctions.NormalizeMethod method,
ScalarValuedFunction expr,
AbstractNumericInfo<?> numInfo)
Create a normalization function for the given function expression.
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static ScalarValuedFunction |
normalizeFunction(StatsFunctions.NormalizeMethod method,
String field,
AbstractNumericInfo<?> numInfo)
Create a normalization function for the given input field.
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static ScalarValuedFunction |
zscore(ScalarValuedFunction expr,
BigDecimal mean,
BigDecimal stddev)
Create a Z-Score normalization function for the given input function.
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static ScalarValuedFunction |
zscore(ScalarValuedFunction expr,
double mean,
double stddev)
Create a Z-Score normalization function for the given input function.
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static ScalarValuedFunction |
zscore(String field,
BigDecimal mean,
BigDecimal stddev)
Create a Z-Score normalization function for the input field.
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static ScalarValuedFunction |
zscore(String field,
double mean,
double stddev)
Create a Z-Score normalization function for the input field.
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public static ScalarValuedFunction normalizeFunction(StatsFunctions.NormalizeMethod method, String field, AbstractNumericInfo<?> numInfo)
method
- the method to usefield
- input field to normalizenumInfo
- numerical statistics of the input fieldpublic static ScalarValuedFunction normalizeFunction(StatsFunctions.NormalizeMethod method, ScalarValuedFunction expr, AbstractNumericInfo<?> numInfo)
method
- the method to useexpr
- apply normalization to the result of this functionnumInfo
- numerical statistics of the input fieldpublic static ScalarValuedFunction zscore(String field, double mean, double stddev)
field
- input field to normalizemean
- mean of the input datastddev
- standard deviation of the input datapublic static ScalarValuedFunction zscore(ScalarValuedFunction expr, double mean, double stddev)
expr
- apply normalization to the result of this functionmean
- mean of the input datastddev
- standard deviation of the input datapublic static ScalarValuedFunction zscore(String field, BigDecimal mean, BigDecimal stddev)
field
- input field to normalizemean
- mean of the input datastddev
- standard deviation of the input datapublic static ScalarValuedFunction zscore(ScalarValuedFunction expr, BigDecimal mean, BigDecimal stddev)
expr
- apply normalization to the result of this functionmean
- mean of the input datastddev
- standard deviation of the input datapublic static ScalarValuedFunction minmax(String field, double min, double max)
field
- input field to normalizemin
- minimum value of the input datamax
- maximum value of the input datapublic static ScalarValuedFunction minmax(ScalarValuedFunction expr, double min, double max)
expr
- apply normalization to the result of this functionmin
- minimum value of the input datamax
- maximum value of the input datapublic static ScalarValuedFunction minmax(String field, BigDecimal min, BigDecimal max)
field
- input field to normalizemin
- minimum value of the input datamax
- maximum value of the input datapublic static ScalarValuedFunction minmax(ScalarValuedFunction expr, BigDecimal min, BigDecimal max)
expr
- apply normalization to the result of this functionmin
- minimum value of the input datamax
- maximum value of the input dataCopyright © 2024 Actian Corporation. All rights reserved.