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<div class="subTitle">org.apache.spark.ml.regression</div>
<h2 title="Interface GeneralizedLinearRegressionBase" class="title">Interface GeneralizedLinearRegressionBase</h2>
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<pre>public interface <span class="typeNameLabel">GeneralizedLinearRegressionBase</span>
extends <a href="../../../../../org/apache/spark/ml/PredictorParams.html" title="interface in org.apache.spark.ml">PredictorParams</a>, <a href="../../../../../org/apache/spark/ml/param/shared/HasFitIntercept.html" title="interface in org.apache.spark.ml.param.shared">HasFitIntercept</a>, <a href="../../../../../org/apache/spark/ml/param/shared/HasMaxIter.html" title="interface in org.apache.spark.ml.param.shared">HasMaxIter</a>, <a href="../../../../../org/apache/spark/ml/param/shared/HasTol.html" title="interface in org.apache.spark.ml.param.shared">HasTol</a>, <a href="../../../../../org/apache/spark/ml/param/shared/HasRegParam.html" title="interface in org.apache.spark.ml.param.shared">HasRegParam</a>, <a href="../../../../../org/apache/spark/ml/param/shared/HasWeightCol.html" title="interface in org.apache.spark.ml.param.shared">HasWeightCol</a>, <a href="../../../../../org/apache/spark/ml/param/shared/HasSolver.html" title="interface in org.apache.spark.ml.param.shared">HasSolver</a>, <a href="../../../../../org/apache/spark/ml/param/shared/HasAggregationDepth.html" title="interface in org.apache.spark.ml.param.shared">HasAggregationDepth</a>, org.apache.spark.internal.Logging</pre>
<div class="block">Params for Generalized Linear Regression.</div>
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<caption><span id="t0" class="activeTableTab"><span>All Methods</span><span class="tabEnd">&nbsp;</span></span><span id="t2" class="tableTab"><span><a href="javascript:show(2);">Instance Methods</a></span><span class="tabEnd">&nbsp;</span></span><span id="t3" class="tableTab"><span><a href="javascript:show(4);">Abstract Methods</a></span><span class="tabEnd">&nbsp;</span></span></caption>
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<th class="colFirst" scope="col">Modifier and Type</th>
<th class="colLast" scope="col">Method and Description</th>
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<td class="colFirst"><code><a href="../../../../../org/apache/spark/ml/param/Param.html" title="class in org.apache.spark.ml.param">Param</a>&lt;String&gt;</code></td>
<td class="colLast"><code><span class="memberNameLink"><a href="../../../../../org/apache/spark/ml/regression/GeneralizedLinearRegressionBase.html#family--">family</a></span>()</code>
<div class="block">Param for the name of family which is a description of the error distribution
to be used in the model.</div>
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<tr id="i1" class="rowColor">
<td class="colFirst"><code>String</code></td>
<td class="colLast"><code><span class="memberNameLink"><a href="../../../../../org/apache/spark/ml/regression/GeneralizedLinearRegressionBase.html#getFamily--">getFamily</a></span>()</code>&nbsp;</td>
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<td class="colFirst"><code>String</code></td>
<td class="colLast"><code><span class="memberNameLink"><a href="../../../../../org/apache/spark/ml/regression/GeneralizedLinearRegressionBase.html#getLink--">getLink</a></span>()</code>&nbsp;</td>
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<td class="colFirst"><code>double</code></td>
<td class="colLast"><code><span class="memberNameLink"><a href="../../../../../org/apache/spark/ml/regression/GeneralizedLinearRegressionBase.html#getLinkPower--">getLinkPower</a></span>()</code>&nbsp;</td>
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<tr id="i4" class="altColor">
<td class="colFirst"><code>String</code></td>
<td class="colLast"><code><span class="memberNameLink"><a href="../../../../../org/apache/spark/ml/regression/GeneralizedLinearRegressionBase.html#getLinkPredictionCol--">getLinkPredictionCol</a></span>()</code>&nbsp;</td>
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<tr id="i5" class="rowColor">
<td class="colFirst"><code>String</code></td>
<td class="colLast"><code><span class="memberNameLink"><a href="../../../../../org/apache/spark/ml/regression/GeneralizedLinearRegressionBase.html#getOffsetCol--">getOffsetCol</a></span>()</code>&nbsp;</td>
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<tr id="i6" class="altColor">
<td class="colFirst"><code>double</code></td>
<td class="colLast"><code><span class="memberNameLink"><a href="../../../../../org/apache/spark/ml/regression/GeneralizedLinearRegressionBase.html#getVariancePower--">getVariancePower</a></span>()</code>&nbsp;</td>
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<tr id="i7" class="rowColor">
<td class="colFirst"><code>boolean</code></td>
<td class="colLast"><code><span class="memberNameLink"><a href="../../../../../org/apache/spark/ml/regression/GeneralizedLinearRegressionBase.html#hasLinkPredictionCol--">hasLinkPredictionCol</a></span>()</code>
<div class="block">Checks whether we should output link prediction.</div>
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<tr id="i8" class="altColor">
<td class="colFirst"><code>boolean</code></td>
<td class="colLast"><code><span class="memberNameLink"><a href="../../../../../org/apache/spark/ml/regression/GeneralizedLinearRegressionBase.html#hasOffsetCol--">hasOffsetCol</a></span>()</code>
<div class="block">Checks whether offset column is set and nonempty.</div>
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<tr id="i9" class="rowColor">
<td class="colFirst"><code>boolean</code></td>
<td class="colLast"><code><span class="memberNameLink"><a href="../../../../../org/apache/spark/ml/regression/GeneralizedLinearRegressionBase.html#hasWeightCol--">hasWeightCol</a></span>()</code>
<div class="block">Checks whether weight column is set and nonempty.</div>
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<tr id="i10" class="altColor">
<td class="colFirst"><code><a href="../../../../../org/apache/spark/ml/param/Param.html" title="class in org.apache.spark.ml.param">Param</a>&lt;String&gt;</code></td>
<td class="colLast"><code><span class="memberNameLink"><a href="../../../../../org/apache/spark/ml/regression/GeneralizedLinearRegressionBase.html#link--">link</a></span>()</code>
<div class="block">Param for the name of link function which provides the relationship
between the linear predictor and the mean of the distribution function.</div>
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<tr id="i11" class="rowColor">
<td class="colFirst"><code><a href="../../../../../org/apache/spark/ml/param/DoubleParam.html" title="class in org.apache.spark.ml.param">DoubleParam</a></code></td>
<td class="colLast"><code><span class="memberNameLink"><a href="../../../../../org/apache/spark/ml/regression/GeneralizedLinearRegressionBase.html#linkPower--">linkPower</a></span>()</code>
<div class="block">Param for the index in the power link function.</div>
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<td class="colFirst"><code><a href="../../../../../org/apache/spark/ml/param/Param.html" title="class in org.apache.spark.ml.param">Param</a>&lt;String&gt;</code></td>
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<div class="block">Param for link prediction (linear predictor) column name.</div>
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<td class="colFirst"><code><a href="../../../../../org/apache/spark/ml/param/Param.html" title="class in org.apache.spark.ml.param">Param</a>&lt;String&gt;</code></td>
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<td class="colFirst"><code><a href="../../../../../org/apache/spark/ml/param/Param.html" title="class in org.apache.spark.ml.param">Param</a>&lt;String&gt;</code></td>
<td class="colLast"><code><span class="memberNameLink"><a href="../../../../../org/apache/spark/ml/regression/GeneralizedLinearRegressionBase.html#solver--">solver</a></span>()</code>
<div class="block">The solver algorithm for optimization.</div>
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<td class="colFirst"><code><a href="../../../../../org/apache/spark/sql/types/StructType.html" title="class in org.apache.spark.sql.types">StructType</a></code></td>
<td class="colLast"><code><span class="memberNameLink"><a href="../../../../../org/apache/spark/ml/regression/GeneralizedLinearRegressionBase.html#validateAndTransformSchema-org.apache.spark.sql.types.StructType-boolean-org.apache.spark.sql.types.DataType-">validateAndTransformSchema</a></span>(<a href="../../../../../org/apache/spark/sql/types/StructType.html" title="class in org.apache.spark.sql.types">StructType</a>&nbsp;schema,
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<div class="block">Validates and transforms the input schema with the provided param map.</div>
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<td class="colFirst"><code><a href="../../../../../org/apache/spark/ml/param/DoubleParam.html" title="class in org.apache.spark.ml.param">DoubleParam</a></code></td>
<td class="colLast"><code><span class="memberNameLink"><a href="../../../../../org/apache/spark/ml/regression/GeneralizedLinearRegressionBase.html#variancePower--">variancePower</a></span>()</code>
<div class="block">Param for the power in the variance function of the Tweedie distribution which provides
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<code>$init$, initializeForcefully, initializeLogIfNecessary, initializeLogIfNecessary, initializeLogIfNecessary$default$2, initLock, isTraceEnabled, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarning, org$apache$spark$internal$Logging$$log__$eq, org$apache$spark$internal$Logging$$log_, uninitialize</code></li>
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<h4>family</h4>
<pre><a href="../../../../../org/apache/spark/ml/param/Param.html" title="class in org.apache.spark.ml.param">Param</a>&lt;String&gt;&nbsp;family()</pre>
<div class="block">Param for the name of family which is a description of the error distribution
to be used in the model.
Supported options: "gaussian", "binomial", "poisson", "gamma" and "tweedie".
Default is "gaussian".
<p></div>
<dl>
<dt><span class="returnLabel">Returns:</span></dt>
<dd>(undocumented)</dd>
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<pre>double&nbsp;getLinkPower()</pre>
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<pre>double&nbsp;getVariancePower()</pre>
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<pre>boolean&nbsp;hasLinkPredictionCol()</pre>
<div class="block">Checks whether we should output link prediction.</div>
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<pre>boolean&nbsp;hasOffsetCol()</pre>
<div class="block">Checks whether offset column is set and nonempty.</div>
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<pre>boolean&nbsp;hasWeightCol()</pre>
<div class="block">Checks whether weight column is set and nonempty.</div>
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<pre><a href="../../../../../org/apache/spark/ml/param/Param.html" title="class in org.apache.spark.ml.param">Param</a>&lt;String&gt;&nbsp;link()</pre>
<div class="block">Param for the name of link function which provides the relationship
between the linear predictor and the mean of the distribution function.
Supported options: "identity", "log", "inverse", "logit", "probit", "cloglog" and "sqrt".
This is used only when family is not "tweedie". The link function for the "tweedie" family
must be specified through <code>linkPower</code>.
<p></div>
<dl>
<dt><span class="returnLabel">Returns:</span></dt>
<dd>(undocumented)</dd>
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<pre><a href="../../../../../org/apache/spark/ml/param/DoubleParam.html" title="class in org.apache.spark.ml.param">DoubleParam</a>&nbsp;linkPower()</pre>
<div class="block">Param for the index in the power link function. Only applicable to the Tweedie family.
Note that link power 0, 1, -1 or 0.5 corresponds to the Log, Identity, Inverse or Sqrt
link, respectively.
When not set, this value defaults to 1 - <code>variancePower</code>, which matches the R "statmod"
package.
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<dt><span class="returnLabel">Returns:</span></dt>
<dd>(undocumented)</dd>
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<pre><a href="../../../../../org/apache/spark/ml/param/Param.html" title="class in org.apache.spark.ml.param">Param</a>&lt;String&gt;&nbsp;linkPredictionCol()</pre>
<div class="block">Param for link prediction (linear predictor) column name.
Default is not set, which means we do not output link prediction.
<p></div>
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<dt><span class="returnLabel">Returns:</span></dt>
<dd>(undocumented)</dd>
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<pre><a href="../../../../../org/apache/spark/ml/param/Param.html" title="class in org.apache.spark.ml.param">Param</a>&lt;String&gt;&nbsp;offsetCol()</pre>
<div class="block">Param for offset column name. If this is not set or empty, we treat all instance offsets
as 0.0. The feature specified as offset has a constant coefficient of 1.0.
<p></div>
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<dt><span class="returnLabel">Returns:</span></dt>
<dd>(undocumented)</dd>
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<pre><a href="../../../../../org/apache/spark/ml/param/Param.html" title="class in org.apache.spark.ml.param">Param</a>&lt;String&gt;&nbsp;solver()</pre>
<div class="block">The solver algorithm for optimization.
Supported options: "irls" (iteratively reweighted least squares).
Default: "irls"
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<dl>
<dt><span class="overrideSpecifyLabel">Specified by:</span></dt>
<dd><code><a href="../../../../../org/apache/spark/ml/param/shared/HasSolver.html#solver--">solver</a></code>&nbsp;in interface&nbsp;<code><a href="../../../../../org/apache/spark/ml/param/shared/HasSolver.html" title="interface in org.apache.spark.ml.param.shared">HasSolver</a></code></dd>
<dt><span class="returnLabel">Returns:</span></dt>
<dd>(undocumented)</dd>
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<pre><a href="../../../../../org/apache/spark/sql/types/StructType.html" title="class in org.apache.spark.sql.types">StructType</a>&nbsp;validateAndTransformSchema(<a href="../../../../../org/apache/spark/sql/types/StructType.html" title="class in org.apache.spark.sql.types">StructType</a>&nbsp;schema,
boolean&nbsp;fitting,
<a href="../../../../../org/apache/spark/sql/types/DataType.html" title="class in org.apache.spark.sql.types">DataType</a>&nbsp;featuresDataType)</pre>
<div class="block"><span class="descfrmTypeLabel">Description copied from interface:&nbsp;<code><a href="../../../../../org/apache/spark/ml/PredictorParams.html#validateAndTransformSchema-org.apache.spark.sql.types.StructType-boolean-org.apache.spark.sql.types.DataType-">PredictorParams</a></code></span></div>
<div class="block">Validates and transforms the input schema with the provided param map.
<p></div>
<dl>
<dt><span class="overrideSpecifyLabel">Specified by:</span></dt>
<dd><code><a href="../../../../../org/apache/spark/ml/PredictorParams.html#validateAndTransformSchema-org.apache.spark.sql.types.StructType-boolean-org.apache.spark.sql.types.DataType-">validateAndTransformSchema</a></code>&nbsp;in interface&nbsp;<code><a href="../../../../../org/apache/spark/ml/PredictorParams.html" title="interface in org.apache.spark.ml">PredictorParams</a></code></dd>
<dt><span class="paramLabel">Parameters:</span></dt>
<dd><code>schema</code> - input schema</dd>
<dd><code>fitting</code> - whether this is in fitting</dd>
<dd><code>featuresDataType</code> - SQL DataType for FeaturesType.
E.g., <code>VectorUDT</code> for vector features.</dd>
<dt><span class="returnLabel">Returns:</span></dt>
<dd>output schema</dd>
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<pre><a href="../../../../../org/apache/spark/ml/param/DoubleParam.html" title="class in org.apache.spark.ml.param">DoubleParam</a>&nbsp;variancePower()</pre>
<div class="block">Param for the power in the variance function of the Tweedie distribution which provides
the relationship between the variance and mean of the distribution.
Only applicable to the Tweedie family.
(see <a href="https://en.wikipedia.org/wiki/Tweedie_distribution">
Tweedie Distribution (Wikipedia)</a>)
Supported values: 0 and [1, Inf).
Note that variance power 0, 1, or 2 corresponds to the Gaussian, Poisson or Gamma
family, respectively.
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<dd>(undocumented)</dd>
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