mirror of https://github.com/apache/lucene.git
SOLR-11947: Remove place holders for documentation that will not be complete for 7.3
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@ -92,8 +92,6 @@ add(fieldA,div(fieldA,fieldB)) // value of fieldA + (value of fieldA / value of
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add(fieldA,if(gt(fieldA,fieldB),fieldA,fieldB)) // if fieldA > fieldB then fieldA + fieldA, else fieldA + fieldB
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add(fieldA,if(gt(fieldA,fieldB),fieldA,fieldB)) // if fieldA > fieldB then fieldA + fieldA, else fieldA + fieldB
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----
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----
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== akima (TODO)
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== analyze
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== analyze
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The `analyze` function analyzes text using a Lucene/Solr analyzer and returns a list of tokens
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The `analyze` function analyzes text using a Lucene/Solr analyzer and returns a list of tokens
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@ -294,9 +292,6 @@ ceil(fieldA) // returns the next highest whole number for fieldA.
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if(gt(fieldA,fieldB),ceil(fieldA),ceil(fieldB)) // if fieldA > fieldB then return the ceil of fieldA, else return the ceil of fieldB.
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if(gt(fieldA,fieldB),ceil(fieldA),ceil(fieldB)) // if fieldA > fieldB then return the ceil of fieldA, else return the ceil of fieldB.
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----
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----
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== chiSquareDataSet (TODO)
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== col
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== col
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The `col` function returns a numeric array from a list of Tuples. The `col`
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The `col` function returns a numeric array from a list of Tuples. The `col`
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@ -524,10 +519,6 @@ A double: the cumulative probability.
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[source,text]
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[source,text]
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cumulativeProbability(normalDistribution(500, 25), 502) // Returns the cumulative probability of the random sample 502 in a normal distribution with a mean of 500 and standard deviation of 25.
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cumulativeProbability(normalDistribution(500, 25), 502) // Returns the cumulative probability of the random sample 502 in a normal distribution with a mean of 500 and standard deviation of 25.
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== density (TODO)
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== derivative
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== derivative
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The `derivative` function returns the https://en.wikipedia.org/wiki/Derivative[derivative] of a function. The derivative function
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The `derivative` function returns the https://en.wikipedia.org/wiki/Derivative[derivative] of a function. The derivative function
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@ -860,9 +851,6 @@ A double.
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factorial(100) //Computes the factorial of 100
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factorial(100) //Computes the factorial of 100
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----
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----
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== featureSelect (TODO)
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== finddelay
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== finddelay
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The `finddelay` function performs a cross-correlation between two numeric arrays and returns the delay.
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The `finddelay` function performs a cross-correlation between two numeric arrays and returns the delay.
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@ -918,8 +906,6 @@ A list of tuples containing the frequency information for each discrete value.
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freqTable(integerArray)
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freqTable(integerArray)
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----
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----
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== fuzzyKmeans (TODO)
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== gammaDistribution
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== gammaDistribution
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The `gammaDistribution` function returns a https://en.wikipedia.org/wiki/Gamma_distribution[gamma probability distribution] based on its parameters. This function is part of the
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The `gammaDistribution` function returns a https://en.wikipedia.org/wiki/Gamma_distribution[gamma probability distribution] based on its parameters. This function is part of the
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@ -998,10 +984,6 @@ getAttributes(matrix)
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map: The map of attributes.
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map: The map of attributes.
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== getCentroids (TODO)
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== getClusters (TODO)
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== getColumnLabels
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== getColumnLabels
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The `getColumnLabels` function returns the columns labels of a matrix. The column labels can be optionally
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The `getColumnLabels` function returns the columns labels of a matrix. The column labels can be optionally
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@ -1019,8 +1001,6 @@ getColumnLabels(matrix)
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string array: The labels for each column in the matrix
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string array: The labels for each column in the matrix
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== getMembershipMatrix (TODO)
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== getRowLabels
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== getRowLabels
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The `getRowLabels` function returns the row labels of a matrix. The row labels can be optionally
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The `getRowLabels` function returns the row labels of a matrix. The row labels can be optionally
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@ -1270,10 +1250,6 @@ A probability distribution function.
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[source,text]
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[source,text]
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logNormalDistribution(.3, .0)
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logNormalDistribution(.3, .0)
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== kmeans (TODO)
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== knn (TODO)
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== kolmogorovSmirnov
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== kolmogorovSmirnov
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The `kolmogorovSmirnov` function performs a https://en.wikipedia.org/wiki/Kolmogorov%E2%80%93Smirnov_test[Kolmogorov Smirnov test],
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The `kolmogorovSmirnov` function performs a https://en.wikipedia.org/wiki/Kolmogorov%E2%80%93Smirnov_test[Kolmogorov Smirnov test],
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@ -1337,9 +1313,6 @@ lteq(fieldA,val(foo)) fieldA <= "foo"
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lteq(add(fieldA,fieldB),6) // fieldA + fieldB <= 6
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lteq(add(fieldA,fieldB),6) // fieldA + fieldB <= 6
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----
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== mannWhitney (TODO)
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== markovChain
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== markovChain
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The `markovChain` function can be used to perform https://en.wikipedia.org/wiki/Markov_chain[Markov Chain] simulations.
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The `markovChain` function can be used to perform https://en.wikipedia.org/wiki/Markov_chain[Markov Chain] simulations.
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@ -1534,11 +1507,6 @@ mult(fieldA,div(fieldA,fieldB)) // value of fieldA * (value of fieldA / value of
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mult(fieldA,if(gt(fieldA,fieldB),fieldA,fieldB)) // if fieldA > fieldB then fieldA * fieldA, else fieldA * fieldB
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mult(fieldA,if(gt(fieldA,fieldB),fieldA,fieldB)) // if fieldA > fieldB then fieldA * fieldA, else fieldA * fieldB
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----
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----
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== multiKmeans (TODO)
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== multiVariateNormalDistribution (TODO)
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== normalDistribution
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== normalDistribution
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The `normalDistribution` function returns a https://en.wikipedia.org/wiki/Normal_distribution[normal probability distribution]
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The `normalDistribution` function returns a https://en.wikipedia.org/wiki/Normal_distribution[normal probability distribution]
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@ -1645,8 +1613,6 @@ or(and(fieldA,fieldB),fieldC) // (fieldA && fieldB) || fieldC
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or(fieldA,fieldB,fieldC,and(fieldD,fieldE),fieldF)
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or(fieldA,fieldB,fieldC,and(fieldD,fieldE),fieldF)
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----
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----
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== pairedTtest (TODO)
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== poissonDistribution
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== poissonDistribution
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The `poissonDistribution` function returns a https://en.wikipedia.org/wiki/Poisson_distribution[poisson probability distribution]
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The `poissonDistribution` function returns a https://en.wikipedia.org/wiki/Poisson_distribution[poisson probability distribution]
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@ -2268,10 +2234,6 @@ sumSq(numericArray)
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numeric: result of the sumSq calculation
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numeric: result of the sumSq calculation
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== termVectors (TODO)
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== topFeatures (TODO)
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== transpose
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== transpose
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The `transpose` function https://en.wikipedia.org/wiki/Transpose[transposes] a matrix .
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The `transpose` function https://en.wikipedia.org/wiki/Transpose[transposes] a matrix .
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@ -2310,8 +2272,6 @@ triangularDistribution(10, 15, 20) // A triangular distribution with a low value
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Probability distribution function
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Probability distribution function
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== ttest (TODO)
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== uniformDistribution
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== uniformDistribution
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The `uniformDistribution` function returns a https://en.wikipedia.org/wiki/Uniform_distribution_(continuous)[continuous uniform probability distribution]
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The `uniformDistribution` function returns a https://en.wikipedia.org/wiki/Uniform_distribution_(continuous)[continuous uniform probability distribution]
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