http://git-wip-us.apache.org/repos/asf/spark-website/blob/6bbac496/site/docs/2.1.2/api/python/_modules/pyspark/ml/param/shared.html ---------------------------------------------------------------------- diff --git a/site/docs/2.1.2/api/python/_modules/pyspark/ml/param/shared.html b/site/docs/2.1.2/api/python/_modules/pyspark/ml/param/shared.html index f2d428f..60e1169 100644 --- a/site/docs/2.1.2/api/python/_modules/pyspark/ml/param/shared.html +++ b/site/docs/2.1.2/api/python/_modules/pyspark/ml/param/shared.html @@ -77,7 +77,7 @@ <span class="n">maxIter</span> <span class="o">=</span> <span class="n">Param</span><span class="p">(</span><span class="n">Params</span><span class="o">.</span><span class="n">_dummy</span><span class="p">(),</span> <span class="s2">"maxIter"</span><span class="p">,</span> <span class="s2">"max number of iterations (>= 0)."</span><span class="p">,</span> <span class="n">typeConverter</span><span class="o">=</span><span class="n">TypeConverters</span><span class="o">.</span><span class="n">toInt</span><span class="p">)</span> <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="nb">super</span><span class="p">(</span><span class="n">HasMaxIter</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="n">__init__</span><span class="p">()</span> + <span class="nb">super</span><span class="p">(</span><span class="n">HasMaxIter</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span> <span class="k">def</span> <span class="nf">setMaxIter</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">value</span><span class="p">):</span> <span class="sd">"""</span> @@ -100,7 +100,7 @@ <span class="n">regParam</span> <span class="o">=</span> <span class="n">Param</span><span class="p">(</span><span class="n">Params</span><span class="o">.</span><span class="n">_dummy</span><span class="p">(),</span> <span class="s2">"regParam"</span><span class="p">,</span> <span class="s2">"regularization parameter (>= 0)."</span><span class="p">,</span> <span class="n">typeConverter</span><span class="o">=</span><span class="n">TypeConverters</span><span class="o">.</span><span class="n">toFloat</span><span class="p">)</span> <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="nb">super</span><span class="p">(</span><span class="n">HasRegParam</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="n">__init__</span><span class="p">()</span> + <span class="nb">super</span><span class="p">(</span><span class="n">HasRegParam</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span> <span class="k">def</span> <span class="nf">setRegParam</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">value</span><span class="p">):</span> <span class="sd">"""</span> @@ -123,7 +123,7 @@ <span class="n">featuresCol</span> <span class="o">=</span> <span class="n">Param</span><span class="p">(</span><span class="n">Params</span><span class="o">.</span><span class="n">_dummy</span><span class="p">(),</span> <span class="s2">"featuresCol"</span><span class="p">,</span> <span class="s2">"features column name."</span><span class="p">,</span> <span class="n">typeConverter</span><span class="o">=</span><span class="n">TypeConverters</span><span class="o">.</span><span class="n">toString</span><span class="p">)</span> <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="nb">super</span><span class="p">(</span><span class="n">HasFeaturesCol</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="n">__init__</span><span class="p">()</span> + <span class="nb">super</span><span class="p">(</span><span class="n">HasFeaturesCol</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span> <span class="bp">self</span><span class="o">.</span><span class="n">_setDefault</span><span class="p">(</span><span class="n">featuresCol</span><span class="o">=</span><span class="s1">'features'</span><span class="p">)</span> <span class="k">def</span> <span class="nf">setFeaturesCol</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">value</span><span class="p">):</span> @@ -147,7 +147,7 @@ <span class="n">labelCol</span> <span class="o">=</span> <span class="n">Param</span><span class="p">(</span><span class="n">Params</span><span class="o">.</span><span class="n">_dummy</span><span class="p">(),</span> <span class="s2">"labelCol"</span><span class="p">,</span> <span class="s2">"label column name."</span><span class="p">,</span> <span class="n">typeConverter</span><span class="o">=</span><span class="n">TypeConverters</span><span class="o">.</span><span class="n">toString</span><span class="p">)</span> <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="nb">super</span><span class="p">(</span><span class="n">HasLabelCol</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="n">__init__</span><span class="p">()</span> + <span class="nb">super</span><span class="p">(</span><span class="n">HasLabelCol</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span> <span class="bp">self</span><span class="o">.</span><span class="n">_setDefault</span><span class="p">(</span><span class="n">labelCol</span><span class="o">=</span><span class="s1">'label'</span><span class="p">)</span> <span class="k">def</span> <span class="nf">setLabelCol</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">value</span><span class="p">):</span> @@ -171,7 +171,7 @@ <span class="n">predictionCol</span> <span class="o">=</span> <span class="n">Param</span><span class="p">(</span><span class="n">Params</span><span class="o">.</span><span class="n">_dummy</span><span class="p">(),</span> <span class="s2">"predictionCol"</span><span class="p">,</span> <span class="s2">"prediction column name."</span><span class="p">,</span> <span class="n">typeConverter</span><span class="o">=</span><span class="n">TypeConverters</span><span class="o">.</span><span class="n">toString</span><span class="p">)</span> <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="nb">super</span><span class="p">(</span><span class="n">HasPredictionCol</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="n">__init__</span><span class="p">()</span> + <span class="nb">super</span><span class="p">(</span><span class="n">HasPredictionCol</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span> <span class="bp">self</span><span class="o">.</span><span class="n">_setDefault</span><span class="p">(</span><span class="n">predictionCol</span><span class="o">=</span><span class="s1">'prediction'</span><span class="p">)</span> <span class="k">def</span> <span class="nf">setPredictionCol</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">value</span><span class="p">):</span> @@ -195,7 +195,7 @@ <span class="n">probabilityCol</span> <span class="o">=</span> <span class="n">Param</span><span class="p">(</span><span class="n">Params</span><span class="o">.</span><span class="n">_dummy</span><span class="p">(),</span> <span class="s2">"probabilityCol"</span><span class="p">,</span> <span class="s2">"Column name for predicted class conditional probabilities. Note: Not all models output well-calibrated probability estimates! These probabilities should be treated as confidences, not precise probabilities."</span><span class="p">,</span> <span class="n">typeConverter</span><span class="o">=</span><span class="n">TypeConverters</span><span class="o">.</span><span class="n">toString</span><span class="p">)</span> <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="nb">super</span><span class="p">(</span><span class="n">HasProbabilityCol</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="n">__init__</span><span class="p">()</span> + <span class="nb">super</span><span class="p">(</span><span class="n">HasProbabilityCol</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span> <span class="bp">self</span><span class="o">.</span><span class="n">_setDefault</span><span class="p">(</span><span class="n">probabilityCol</span><span class="o">=</span><span class="s1">'probability'</span><span class="p">)</span> <span class="k">def</span> <span class="nf">setProbabilityCol</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">value</span><span class="p">):</span> @@ -219,7 +219,7 @@ <span class="n">rawPredictionCol</span> <span class="o">=</span> <span class="n">Param</span><span class="p">(</span><span class="n">Params</span><span class="o">.</span><span class="n">_dummy</span><span class="p">(),</span> <span class="s2">"rawPredictionCol"</span><span class="p">,</span> <span class="s2">"raw prediction (a.k.a. confidence) column name."</span><span class="p">,</span> <span class="n">typeConverter</span><span class="o">=</span><span class="n">TypeConverters</span><span class="o">.</span><span class="n">toString</span><span class="p">)</span> <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="nb">super</span><span class="p">(</span><span class="n">HasRawPredictionCol</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="n">__init__</span><span class="p">()</span> + <span class="nb">super</span><span class="p">(</span><span class="n">HasRawPredictionCol</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span> <span class="bp">self</span><span class="o">.</span><span class="n">_setDefault</span><span class="p">(</span><span class="n">rawPredictionCol</span><span class="o">=</span><span class="s1">'rawPrediction'</span><span class="p">)</span> <span class="k">def</span> <span class="nf">setRawPredictionCol</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">value</span><span class="p">):</span> @@ -243,7 +243,7 @@ <span class="n">inputCol</span> <span class="o">=</span> <span class="n">Param</span><span class="p">(</span><span class="n">Params</span><span class="o">.</span><span class="n">_dummy</span><span class="p">(),</span> <span class="s2">"inputCol"</span><span class="p">,</span> <span class="s2">"input column name."</span><span class="p">,</span> <span class="n">typeConverter</span><span class="o">=</span><span class="n">TypeConverters</span><span class="o">.</span><span class="n">toString</span><span class="p">)</span> <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="nb">super</span><span class="p">(</span><span class="n">HasInputCol</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="n">__init__</span><span class="p">()</span> + <span class="nb">super</span><span class="p">(</span><span class="n">HasInputCol</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span> <span class="k">def</span> <span class="nf">setInputCol</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">value</span><span class="p">):</span> <span class="sd">"""</span> @@ -266,7 +266,7 @@ <span class="n">inputCols</span> <span class="o">=</span> <span class="n">Param</span><span class="p">(</span><span class="n">Params</span><span class="o">.</span><span class="n">_dummy</span><span class="p">(),</span> <span class="s2">"inputCols"</span><span class="p">,</span> <span class="s2">"input column names."</span><span class="p">,</span> <span class="n">typeConverter</span><span class="o">=</span><span class="n">TypeConverters</span><span class="o">.</span><span class="n">toListString</span><span class="p">)</span> <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="nb">super</span><span class="p">(</span><span class="n">HasInputCols</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="n">__init__</span><span class="p">()</span> + <span class="nb">super</span><span class="p">(</span><span class="n">HasInputCols</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span> <span class="k">def</span> <span class="nf">setInputCols</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">value</span><span class="p">):</span> <span class="sd">"""</span> @@ -289,7 +289,7 @@ <span class="n">outputCol</span> <span class="o">=</span> <span class="n">Param</span><span class="p">(</span><span class="n">Params</span><span class="o">.</span><span class="n">_dummy</span><span class="p">(),</span> <span class="s2">"outputCol"</span><span class="p">,</span> <span class="s2">"output column name."</span><span class="p">,</span> <span class="n">typeConverter</span><span class="o">=</span><span class="n">TypeConverters</span><span class="o">.</span><span class="n">toString</span><span class="p">)</span> <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="nb">super</span><span class="p">(</span><span class="n">HasOutputCol</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="n">__init__</span><span class="p">()</span> + <span class="nb">super</span><span class="p">(</span><span class="n">HasOutputCol</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span> <span class="bp">self</span><span class="o">.</span><span class="n">_setDefault</span><span class="p">(</span><span class="n">outputCol</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">uid</span> <span class="o">+</span> <span class="s1">'__output'</span><span class="p">)</span> <span class="k">def</span> <span class="nf">setOutputCol</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">value</span><span class="p">):</span> @@ -313,7 +313,7 @@ <span class="n">numFeatures</span> <span class="o">=</span> <span class="n">Param</span><span class="p">(</span><span class="n">Params</span><span class="o">.</span><span class="n">_dummy</span><span class="p">(),</span> <span class="s2">"numFeatures"</span><span class="p">,</span> <span class="s2">"number of features."</span><span class="p">,</span> <span class="n">typeConverter</span><span class="o">=</span><span class="n">TypeConverters</span><span class="o">.</span><span class="n">toInt</span><span class="p">)</span> <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="nb">super</span><span class="p">(</span><span class="n">HasNumFeatures</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="n">__init__</span><span class="p">()</span> + <span class="nb">super</span><span class="p">(</span><span class="n">HasNumFeatures</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span> <span class="k">def</span> <span class="nf">setNumFeatures</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">value</span><span class="p">):</span> <span class="sd">"""</span> @@ -336,7 +336,7 @@ <span class="n">checkpointInterval</span> <span class="o">=</span> <span class="n">Param</span><span class="p">(</span><span class="n">Params</span><span class="o">.</span><span class="n">_dummy</span><span class="p">(),</span> <span class="s2">"checkpointInterval"</span><span class="p">,</span> <span class="s2">"set checkpoint interval (>= 1) or disable checkpoint (-1). E.g. 10 means that the cache will get checkpointed every 10 iterations."</span><span class="p">,</span> <span class="n">typeConverter</span><span class="o">=</span><span class="n">TypeConverters</span><span class="o">.</span><span class="n">toInt</span><span class="p">)</span> <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="nb">super</span><span class="p">(</span><span class="n">HasCheckpointInterval</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="n">__init__</span><span class="p">()</span> + <span class="nb">super</span><span class="p">(</span><span class="n">HasCheckpointInterval</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span> <span class="k">def</span> <span class="nf">setCheckpointInterval</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">value</span><span class="p">):</span> <span class="sd">"""</span> @@ -359,8 +359,8 @@ <span class="n">seed</span> <span class="o">=</span> <span class="n">Param</span><span class="p">(</span><span class="n">Params</span><span class="o">.</span><span class="n">_dummy</span><span class="p">(),</span> <span class="s2">"seed"</span><span class="p">,</span> <span class="s2">"random seed."</span><span class="p">,</span> <span class="n">typeConverter</span><span class="o">=</span><span class="n">TypeConverters</span><span class="o">.</span><span class="n">toInt</span><span class="p">)</span> <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="nb">super</span><span class="p">(</span><span class="n">HasSeed</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="n">__init__</span><span class="p">()</span> - <span class="bp">self</span><span class="o">.</span><span class="n">_setDefault</span><span class="p">(</span><span class="n">seed</span><span class="o">=</span><span class="nb">hash</span><span class="p">(</span><span class="nb">type</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="n">__name__</span><span class="p">))</span> + <span class="nb">super</span><span class="p">(</span><span class="n">HasSeed</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span> + <span class="bp">self</span><span class="o">.</span><span class="n">_setDefault</span><span class="p">(</span><span class="n">seed</span><span class="o">=</span><span class="nb">hash</span><span class="p">(</span><span class="nb">type</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="vm">__name__</span><span class="p">))</span> <span class="k">def</span> <span class="nf">setSeed</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">value</span><span class="p">):</span> <span class="sd">"""</span> @@ -383,7 +383,7 @@ <span class="n">tol</span> <span class="o">=</span> <span class="n">Param</span><span class="p">(</span><span class="n">Params</span><span class="o">.</span><span class="n">_dummy</span><span class="p">(),</span> <span class="s2">"tol"</span><span class="p">,</span> <span class="s2">"the convergence tolerance for iterative algorithms (>= 0)."</span><span class="p">,</span> <span class="n">typeConverter</span><span class="o">=</span><span class="n">TypeConverters</span><span class="o">.</span><span class="n">toFloat</span><span class="p">)</span> <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="nb">super</span><span class="p">(</span><span class="n">HasTol</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="n">__init__</span><span class="p">()</span> + <span class="nb">super</span><span class="p">(</span><span class="n">HasTol</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span> <span class="k">def</span> <span class="nf">setTol</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">value</span><span class="p">):</span> <span class="sd">"""</span> @@ -406,7 +406,7 @@ <span class="n">stepSize</span> <span class="o">=</span> <span class="n">Param</span><span class="p">(</span><span class="n">Params</span><span class="o">.</span><span class="n">_dummy</span><span class="p">(),</span> <span class="s2">"stepSize"</span><span class="p">,</span> <span class="s2">"Step size to be used for each iteration of optimization (>= 0)."</span><span class="p">,</span> <span class="n">typeConverter</span><span class="o">=</span><span class="n">TypeConverters</span><span class="o">.</span><span class="n">toFloat</span><span class="p">)</span> <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="nb">super</span><span class="p">(</span><span class="n">HasStepSize</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="n">__init__</span><span class="p">()</span> + <span class="nb">super</span><span class="p">(</span><span class="n">HasStepSize</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span> <span class="k">def</span> <span class="nf">setStepSize</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">value</span><span class="p">):</span> <span class="sd">"""</span> @@ -429,7 +429,7 @@ <span class="n">handleInvalid</span> <span class="o">=</span> <span class="n">Param</span><span class="p">(</span><span class="n">Params</span><span class="o">.</span><span class="n">_dummy</span><span class="p">(),</span> <span class="s2">"handleInvalid"</span><span class="p">,</span> <span class="s2">"how to handle invalid entries. Options are skip (which will filter out rows with bad values), or error (which will throw an error). More options may be added later."</span><span class="p">,</span> <span class="n">typeConverter</span><span class="o">=</span><span class="n">TypeConverters</span><span class="o">.</span><span class="n">toString</span><span class="p">)</span> <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="nb">super</span><span class="p">(</span><span class="n">HasHandleInvalid</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="n">__init__</span><span class="p">()</span> + <span class="nb">super</span><span class="p">(</span><span class="n">HasHandleInvalid</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span> <span class="k">def</span> <span class="nf">setHandleInvalid</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">value</span><span class="p">):</span> <span class="sd">"""</span> @@ -452,7 +452,7 @@ <span class="n">elasticNetParam</span> <span class="o">=</span> <span class="n">Param</span><span class="p">(</span><span class="n">Params</span><span class="o">.</span><span class="n">_dummy</span><span class="p">(),</span> <span class="s2">"elasticNetParam"</span><span class="p">,</span> <span class="s2">"the ElasticNet mixing parameter, in range [0, 1]. For alpha = 0, the penalty is an L2 penalty. For alpha = 1, it is an L1 penalty."</span><span class="p">,</span> <span class="n">typeConverter</span><span class="o">=</span><span class="n">TypeConverters</span><span class="o">.</span><span class="n">toFloat</span><span class="p">)</span> <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="nb">super</span><span class="p">(</span><span class="n">HasElasticNetParam</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="n">__init__</span><span class="p">()</span> + <span class="nb">super</span><span class="p">(</span><span class="n">HasElasticNetParam</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span> <span class="bp">self</span><span class="o">.</span><span class="n">_setDefault</span><span class="p">(</span><span class="n">elasticNetParam</span><span class="o">=</span><span class="mf">0.0</span><span class="p">)</span> <span class="k">def</span> <span class="nf">setElasticNetParam</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">value</span><span class="p">):</span> @@ -476,7 +476,7 @@ <span class="n">fitIntercept</span> <span class="o">=</span> <span class="n">Param</span><span class="p">(</span><span class="n">Params</span><span class="o">.</span><span class="n">_dummy</span><span class="p">(),</span> <span class="s2">"fitIntercept"</span><span class="p">,</span> <span class="s2">"whether to fit an intercept term."</span><span class="p">,</span> <span class="n">typeConverter</span><span class="o">=</span><span class="n">TypeConverters</span><span class="o">.</span><span class="n">toBoolean</span><span class="p">)</span> <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="nb">super</span><span class="p">(</span><span class="n">HasFitIntercept</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="n">__init__</span><span class="p">()</span> + <span class="nb">super</span><span class="p">(</span><span class="n">HasFitIntercept</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span> <span class="bp">self</span><span class="o">.</span><span class="n">_setDefault</span><span class="p">(</span><span class="n">fitIntercept</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span> <span class="k">def</span> <span class="nf">setFitIntercept</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">value</span><span class="p">):</span> @@ -500,7 +500,7 @@ <span class="n">standardization</span> <span class="o">=</span> <span class="n">Param</span><span class="p">(</span><span class="n">Params</span><span class="o">.</span><span class="n">_dummy</span><span class="p">(),</span> <span class="s2">"standardization"</span><span class="p">,</span> <span class="s2">"whether to standardize the training features before fitting the model."</span><span class="p">,</span> <span class="n">typeConverter</span><span class="o">=</span><span class="n">TypeConverters</span><span class="o">.</span><span class="n">toBoolean</span><span class="p">)</span> <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="nb">super</span><span class="p">(</span><span class="n">HasStandardization</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="n">__init__</span><span class="p">()</span> + <span class="nb">super</span><span class="p">(</span><span class="n">HasStandardization</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span> <span class="bp">self</span><span class="o">.</span><span class="n">_setDefault</span><span class="p">(</span><span class="n">standardization</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span> <span class="k">def</span> <span class="nf">setStandardization</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">value</span><span class="p">):</span> @@ -524,7 +524,7 @@ <span class="n">thresholds</span> <span class="o">=</span> <span class="n">Param</span><span class="p">(</span><span class="n">Params</span><span class="o">.</span><span class="n">_dummy</span><span class="p">(),</span> <span class="s2">"thresholds"</span><span class="p">,</span> <span class="s2">"Thresholds in multi-class classification to adjust the probability of predicting each class. Array must have length equal to the number of classes, with values > 0, excepting that at most one value may be 0. The class with largest value p/t is predicted, where p is the original probability of that class and t is the class's threshold."</span><span class="p">,</span> <span class="n">typeConverter</span><span class="o">=</span><span class="n">TypeConverters</span><span class="o">.</span><span class="n">toListFloat</span><span class="p">)</span> <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="nb">super</span><span class="p">(</span><span class="n">HasThresholds</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="n">__init__</span><span class="p">()</span> + <span class="nb">super</span><span class="p">(</span><span class="n">HasThresholds</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span> <span class="k">def</span> <span class="nf">setThresholds</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">value</span><span class="p">):</span> <span class="sd">"""</span> @@ -547,7 +547,7 @@ <span class="n">weightCol</span> <span class="o">=</span> <span class="n">Param</span><span class="p">(</span><span class="n">Params</span><span class="o">.</span><span class="n">_dummy</span><span class="p">(),</span> <span class="s2">"weightCol"</span><span class="p">,</span> <span class="s2">"weight column name. If this is not set or empty, we treat all instance weights as 1.0."</span><span class="p">,</span> <span class="n">typeConverter</span><span class="o">=</span><span class="n">TypeConverters</span><span class="o">.</span><span class="n">toString</span><span class="p">)</span> <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="nb">super</span><span class="p">(</span><span class="n">HasWeightCol</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="n">__init__</span><span class="p">()</span> + <span class="nb">super</span><span class="p">(</span><span class="n">HasWeightCol</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span> <span class="k">def</span> <span class="nf">setWeightCol</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">value</span><span class="p">):</span> <span class="sd">"""</span> @@ -570,7 +570,7 @@ <span class="n">solver</span> <span class="o">=</span> <span class="n">Param</span><span class="p">(</span><span class="n">Params</span><span class="o">.</span><span class="n">_dummy</span><span class="p">(),</span> <span class="s2">"solver"</span><span class="p">,</span> <span class="s2">"the solver algorithm for optimization. If this is not set or empty, default value is 'auto'."</span><span class="p">,</span> <span class="n">typeConverter</span><span class="o">=</span><span class="n">TypeConverters</span><span class="o">.</span><span class="n">toString</span><span class="p">)</span> <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="nb">super</span><span class="p">(</span><span class="n">HasSolver</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="n">__init__</span><span class="p">()</span> + <span class="nb">super</span><span class="p">(</span><span class="n">HasSolver</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span> <span class="bp">self</span><span class="o">.</span><span class="n">_setDefault</span><span class="p">(</span><span class="n">solver</span><span class="o">=</span><span class="s1">'auto'</span><span class="p">)</span> <span class="k">def</span> <span class="nf">setSolver</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">value</span><span class="p">):</span> @@ -594,7 +594,7 @@ <span class="n">varianceCol</span> <span class="o">=</span> <span class="n">Param</span><span class="p">(</span><span class="n">Params</span><span class="o">.</span><span class="n">_dummy</span><span class="p">(),</span> <span class="s2">"varianceCol"</span><span class="p">,</span> <span class="s2">"column name for the biased sample variance of prediction."</span><span class="p">,</span> <span class="n">typeConverter</span><span class="o">=</span><span class="n">TypeConverters</span><span class="o">.</span><span class="n">toString</span><span class="p">)</span> <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="nb">super</span><span class="p">(</span><span class="n">HasVarianceCol</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="n">__init__</span><span class="p">()</span> + <span class="nb">super</span><span class="p">(</span><span class="n">HasVarianceCol</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span> <span class="k">def</span> <span class="nf">setVarianceCol</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">value</span><span class="p">):</span> <span class="sd">"""</span> @@ -617,7 +617,7 @@ <span class="n">aggregationDepth</span> <span class="o">=</span> <span class="n">Param</span><span class="p">(</span><span class="n">Params</span><span class="o">.</span><span class="n">_dummy</span><span class="p">(),</span> <span class="s2">"aggregationDepth"</span><span class="p">,</span> <span class="s2">"suggested depth for treeAggregate (>= 2)."</span><span class="p">,</span> <span class="n">typeConverter</span><span class="o">=</span><span class="n">TypeConverters</span><span class="o">.</span><span class="n">toInt</span><span class="p">)</span> <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="nb">super</span><span class="p">(</span><span class="n">HasAggregationDepth</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="n">__init__</span><span class="p">()</span> + <span class="nb">super</span><span class="p">(</span><span class="n">HasAggregationDepth</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span> <span class="bp">self</span><span class="o">.</span><span class="n">_setDefault</span><span class="p">(</span><span class="n">aggregationDepth</span><span class="o">=</span><span class="mi">2</span><span class="p">)</span> <span class="k">def</span> <span class="nf">setAggregationDepth</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">value</span><span class="p">):</span> @@ -647,7 +647,7 @@ <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> - <span class="nb">super</span><span class="p">(</span><span class="n">DecisionTreeParams</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="n">__init__</span><span class="p">()</span> + <span class="nb">super</span><span class="p">(</span><span class="n">DecisionTreeParams</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span> <span class="k">def</span> <span class="nf">setMaxDepth</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">value</span><span class="p">):</span> <span class="sd">"""</span>
http://git-wip-us.apache.org/repos/asf/spark-website/blob/6bbac496/site/docs/2.1.2/api/python/_modules/pyspark/ml/pipeline.html ---------------------------------------------------------------------- diff --git a/site/docs/2.1.2/api/python/_modules/pyspark/ml/pipeline.html b/site/docs/2.1.2/api/python/_modules/pyspark/ml/pipeline.html index c67138a..9abb3d8 100644 --- a/site/docs/2.1.2/api/python/_modules/pyspark/ml/pipeline.html +++ b/site/docs/2.1.2/api/python/_modules/pyspark/ml/pipeline.html @@ -105,7 +105,7 @@ <span class="sd">"""</span> <span class="sd"> __init__(self, stages=None)</span> <span class="sd"> """</span> - <span class="nb">super</span><span class="p">(</span><span class="n">Pipeline</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="n">__init__</span><span class="p">()</span> + <span class="nb">super</span><span class="p">(</span><span class="n">Pipeline</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span> <span class="n">kwargs</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_input_kwargs</span> <span class="bp">self</span><span class="o">.</span><span class="n">setParams</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span> @@ -187,18 +187,18 @@ <span class="nd">@classmethod</span> <span class="nd">@since</span><span class="p">(</span><span class="s2">"2.0.0"</span><span class="p">)</span> -<div class="viewcode-block" id="Pipeline.read"><a class="viewcode-back" href="../../../pyspark.ml.html#pyspark.ml.Pipeline.read">[docs]</a> <span class="k">def</span> <span class="nf">read</span><span class="p">(</span><span class="n">cls</span><span class="p">):</span> +<div class="viewcode-block" id="Pipeline.read"><a class="viewcode-back" href="../../../pyspark.ml.html#pyspark.ml.Pipeline.read">[docs]</a> <span class="k">def</span> <span class="nf">read</span><span class="p">(</span><span class="bp">cls</span><span class="p">):</span> <span class="sd">"""Returns an MLReader instance for this class."""</span> - <span class="k">return</span> <span class="n">JavaMLReader</span><span class="p">(</span><span class="n">cls</span><span class="p">)</span></div> + <span class="k">return</span> <span class="n">JavaMLReader</span><span class="p">(</span><span class="bp">cls</span><span class="p">)</span></div> <span class="nd">@classmethod</span> - <span class="k">def</span> <span class="nf">_from_java</span><span class="p">(</span><span class="n">cls</span><span class="p">,</span> <span class="n">java_stage</span><span class="p">):</span> + <span class="k">def</span> <span class="nf">_from_java</span><span class="p">(</span><span class="bp">cls</span><span class="p">,</span> <span class="n">java_stage</span><span class="p">):</span> <span class="sd">"""</span> <span class="sd"> Given a Java Pipeline, create and return a Python wrapper of it.</span> <span class="sd"> Used for ML persistence.</span> <span class="sd"> """</span> <span class="c1"># Create a new instance of this stage.</span> - <span class="n">py_stage</span> <span class="o">=</span> <span class="n">cls</span><span class="p">()</span> + <span class="n">py_stage</span> <span class="o">=</span> <span class="bp">cls</span><span class="p">()</span> <span class="c1"># Load information from java_stage to the instance.</span> <span class="n">py_stages</span> <span class="o">=</span> <span class="p">[</span><span class="n">JavaParams</span><span class="o">.</span><span class="n">_from_java</span><span class="p">(</span><span class="n">s</span><span class="p">)</span> <span class="k">for</span> <span class="n">s</span> <span class="ow">in</span> <span class="n">java_stage</span><span class="o">.</span><span class="n">getStages</span><span class="p">()]</span> <span class="n">py_stage</span><span class="o">.</span><span class="n">setStages</span><span class="p">(</span><span class="n">py_stages</span><span class="p">)</span> @@ -213,8 +213,8 @@ <span class="sd"> """</span> <span class="n">gateway</span> <span class="o">=</span> <span class="n">SparkContext</span><span class="o">.</span><span class="n">_gateway</span> - <span class="n">cls</span> <span class="o">=</span> <span class="n">SparkContext</span><span class="o">.</span><span class="n">_jvm</span><span class="o">.</span><span class="n">org</span><span class="o">.</span><span class="n">apache</span><span class="o">.</span><span class="n">spark</span><span class="o">.</span><span class="n">ml</span><span class="o">.</span><span class="n">PipelineStage</span> - <span class="n">java_stages</span> <span class="o">=</span> <span class="n">gateway</span><span class="o">.</span><span class="n">new_array</span><span class="p">(</span><span class="n">cls</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">getStages</span><span class="p">()))</span> + <span class="bp">cls</span> <span class="o">=</span> <span class="n">SparkContext</span><span class="o">.</span><span class="n">_jvm</span><span class="o">.</span><span class="n">org</span><span class="o">.</span><span class="n">apache</span><span class="o">.</span><span class="n">spark</span><span class="o">.</span><span class="n">ml</span><span class="o">.</span><span class="n">PipelineStage</span> + <span class="n">java_stages</span> <span class="o">=</span> <span class="n">gateway</span><span class="o">.</span><span class="n">new_array</span><span class="p">(</span><span class="bp">cls</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">getStages</span><span class="p">()))</span> <span class="k">for</span> <span class="n">idx</span><span class="p">,</span> <span class="n">stage</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">getStages</span><span class="p">()):</span> <span class="n">java_stages</span><span class="p">[</span><span class="n">idx</span><span class="p">]</span> <span class="o">=</span> <span class="n">stage</span><span class="o">.</span><span class="n">_to_java</span><span class="p">()</span> @@ -233,7 +233,7 @@ <span class="sd"> """</span> <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">stages</span><span class="p">):</span> - <span class="nb">super</span><span class="p">(</span><span class="n">PipelineModel</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="n">__init__</span><span class="p">()</span> + <span class="nb">super</span><span class="p">(</span><span class="n">PipelineModel</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span> <span class="bp">self</span><span class="o">.</span><span class="n">stages</span> <span class="o">=</span> <span class="n">stages</span> <span class="k">def</span> <span class="nf">_transform</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">dataset</span><span class="p">):</span> @@ -266,12 +266,12 @@ <span class="nd">@classmethod</span> <span class="nd">@since</span><span class="p">(</span><span class="s2">"2.0.0"</span><span class="p">)</span> -<div class="viewcode-block" id="PipelineModel.read"><a class="viewcode-back" href="../../../pyspark.ml.html#pyspark.ml.PipelineModel.read">[docs]</a> <span class="k">def</span> <span class="nf">read</span><span class="p">(</span><span class="n">cls</span><span class="p">):</span> +<div class="viewcode-block" id="PipelineModel.read"><a class="viewcode-back" href="../../../pyspark.ml.html#pyspark.ml.PipelineModel.read">[docs]</a> <span class="k">def</span> <span class="nf">read</span><span class="p">(</span><span class="bp">cls</span><span class="p">):</span> <span class="sd">"""Returns an MLReader instance for this class."""</span> - <span class="k">return</span> <span class="n">JavaMLReader</span><span class="p">(</span><span class="n">cls</span><span class="p">)</span></div> + <span class="k">return</span> <span class="n">JavaMLReader</span><span class="p">(</span><span class="bp">cls</span><span class="p">)</span></div> <span class="nd">@classmethod</span> - <span class="k">def</span> <span class="nf">_from_java</span><span class="p">(</span><span class="n">cls</span><span class="p">,</span> <span class="n">java_stage</span><span class="p">):</span> + <span class="k">def</span> <span class="nf">_from_java</span><span class="p">(</span><span class="bp">cls</span><span class="p">,</span> <span class="n">java_stage</span><span class="p">):</span> <span class="sd">"""</span> <span class="sd"> Given a Java PipelineModel, create and return a Python wrapper of it.</span> <span class="sd"> Used for ML persistence.</span> @@ -279,7 +279,7 @@ <span class="c1"># Load information from java_stage to the instance.</span> <span class="n">py_stages</span> <span class="o">=</span> <span class="p">[</span><span class="n">JavaParams</span><span class="o">.</span><span class="n">_from_java</span><span class="p">(</span><span class="n">s</span><span class="p">)</span> <span class="k">for</span> <span class="n">s</span> <span class="ow">in</span> <span class="n">java_stage</span><span class="o">.</span><span class="n">stages</span><span class="p">()]</span> <span class="c1"># Create a new instance of this stage.</span> - <span class="n">py_stage</span> <span class="o">=</span> <span class="n">cls</span><span class="p">(</span><span class="n">py_stages</span><span class="p">)</span> + <span class="n">py_stage</span> <span class="o">=</span> <span class="bp">cls</span><span class="p">(</span><span class="n">py_stages</span><span class="p">)</span> <span class="n">py_stage</span><span class="o">.</span><span class="n">_resetUid</span><span class="p">(</span><span class="n">java_stage</span><span class="o">.</span><span class="n">uid</span><span class="p">())</span> <span class="k">return</span> <span class="n">py_stage</span> @@ -291,8 +291,8 @@ <span class="sd"> """</span> <span class="n">gateway</span> <span class="o">=</span> <span class="n">SparkContext</span><span class="o">.</span><span class="n">_gateway</span> - <span class="n">cls</span> <span class="o">=</span> <span class="n">SparkContext</span><span class="o">.</span><span class="n">_jvm</span><span class="o">.</span><span class="n">org</span><span class="o">.</span><span class="n">apache</span><span class="o">.</span><span class="n">spark</span><span class="o">.</span><span class="n">ml</span><span class="o">.</span><span class="n">Transformer</span> - <span class="n">java_stages</span> <span class="o">=</span> <span class="n">gateway</span><span class="o">.</span><span class="n">new_array</span><span class="p">(</span><span class="n">cls</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">stages</span><span class="p">))</span> + <span class="bp">cls</span> <span class="o">=</span> <span class="n">SparkContext</span><span class="o">.</span><span class="n">_jvm</span><span class="o">.</span><span class="n">org</span><span class="o">.</span><span class="n">apache</span><span class="o">.</span><span class="n">spark</span><span class="o">.</span><span class="n">ml</span><span class="o">.</span><span class="n">Transformer</span> + <span class="n">java_stages</span> <span class="o">=</span> <span class="n">gateway</span><span class="o">.</span><span class="n">new_array</span><span class="p">(</span><span class="bp">cls</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">stages</span><span class="p">))</span> <span class="k">for</span> <span class="n">idx</span><span class="p">,</span> <span class="n">stage</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">stages</span><span class="p">):</span> <span class="n">java_stages</span><span class="p">[</span><span class="n">idx</span><span class="p">]</span> <span class="o">=</span> <span class="n">stage</span><span class="o">.</span><span class="n">_to_java</span><span class="p">()</span> http://git-wip-us.apache.org/repos/asf/spark-website/blob/6bbac496/site/docs/2.1.2/api/python/_modules/pyspark/ml/recommendation.html ---------------------------------------------------------------------- diff --git a/site/docs/2.1.2/api/python/_modules/pyspark/ml/recommendation.html b/site/docs/2.1.2/api/python/_modules/pyspark/ml/recommendation.html index 418bda9..341a456 100644 --- a/site/docs/2.1.2/api/python/_modules/pyspark/ml/recommendation.html +++ b/site/docs/2.1.2/api/python/_modules/pyspark/ml/recommendation.html @@ -187,7 +187,7 @@ <span class="sd"> intermediateStorageLevel="MEMORY_AND_DISK", \</span> <span class="sd"> finalStorageLevel="MEMORY_AND_DISK")</span> <span class="sd"> """</span> - <span class="nb">super</span><span class="p">(</span><span class="n">ALS</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="n">__init__</span><span class="p">()</span> + <span class="nb">super</span><span class="p">(</span><span class="n">ALS</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span> <span class="bp">self</span><span class="o">.</span><span class="n">_java_obj</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_new_java_obj</span><span class="p">(</span><span class="s2">"org.apache.spark.ml.recommendation.ALS"</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">uid</span><span class="p">)</span> <span class="bp">self</span><span class="o">.</span><span class="n">_setDefault</span><span class="p">(</span><span class="n">rank</span><span class="o">=</span><span class="mi">10</span><span class="p">,</span> <span class="n">maxIter</span><span class="o">=</span><span class="mi">10</span><span class="p">,</span> <span class="n">regParam</span><span class="o">=</span><span class="mf">0.1</span><span class="p">,</span> <span class="n">numUserBlocks</span><span class="o">=</span><span class="mi">10</span><span class="p">,</span> <span class="n">numItemBlocks</span><span class="o">=</span><span class="mi">10</span><span class="p">,</span> <span class="n">implicitPrefs</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=</span><span class="mf">1.0</span><span class="p">,</span> <span class="n">userCol</span><span class="o">=</span><span class="s2">"user"</span><span class="p">,</span> <span class="n">itemCol</span><span class="o">=</span><span class="s2">"item"</span><span class="p">,</span> @@ -413,11 +413,11 @@ <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_call_java</span><span class="p">(</span><span class="s2">"itemFactors"</span><span class="p">)</span></div> -<span class="k">if</span> <span class="n">__name__</span> <span class="o">==</span> <span class="s2">"__main__"</span><span class="p">:</span> +<span class="k">if</span> <span class="vm">__name__</span> <span class="o">==</span> <span class="s2">"__main__"</span><span class="p">:</span> <span class="kn">import</span> <span class="nn">doctest</span> <span class="kn">import</span> <span class="nn">pyspark.ml.recommendation</span> <span class="kn">from</span> <span class="nn">pyspark.sql</span> <span class="k">import</span> <span class="n">SparkSession</span> - <span class="n">globs</span> <span class="o">=</span> <span class="n">pyspark</span><span class="o">.</span><span class="n">ml</span><span class="o">.</span><span class="n">recommendation</span><span class="o">.</span><span class="n">__dict__</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span> + <span class="n">globs</span> <span class="o">=</span> <span class="n">pyspark</span><span class="o">.</span><span class="n">ml</span><span class="o">.</span><span class="n">recommendation</span><span class="o">.</span><span class="vm">__dict__</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span> <span class="c1"># The small batch size here ensures that we see multiple batches,</span> <span class="c1"># even in these small test examples:</span> <span class="n">spark</span> <span class="o">=</span> <span class="n">SparkSession</span><span class="o">.</span><span class="n">builder</span>\ --------------------------------------------------------------------- To unsubscribe, e-mail: commits-unsubscr...@spark.apache.org For additional commands, e-mail: commits-h...@spark.apache.org