Elastic Net: Remove buggy doc example

src/ports/postgres/modules/elastic_net/elastic_net.sql_in

@@ -36,7 +36,7 @@ This module implements elastic net regularization for linear and logistic regres
 @anchor help
 @par Online Help
 
-View a summary of the Elastic Net Regularization Module by calling the \ref elastic_net_train() function with no arguments: 
+View a summary of the Elastic Net Regularization Module by calling the \ref elastic_net_train() function with no arguments:
 @verbatim
 SELECT madlib.elastic_net_train();
 @endverbatim
@@ -46,19 +46,19 @@ SELECT madlib.elastic_net_train();
 The training function has the following syntax:
 @verbatim
 elastic_net_train(
-    tbl_source, 
-    tbl_result, 
-    col_dep_var, 
+    tbl_source,
+    tbl_result,
+    col_dep_var,
     col_ind_var,
-    regress_family, 
-    alpha, 
-    lambda_value, 
+    regress_family,
+    alpha,
+    lambda_value,
     standardize,
-    grouping_col, 
+    grouping_col,
     optimizer,
-    optimizer_params, 
+    optimizer_params,
     excluded,
-    max_iter, 
+    max_iter,
     tolerance)
 @endverbatim
 \note It is \b strongly \b recommended that you run
@@ -139,14 +139,14 @@ to specify the value of a parameter, otherwise the parameter is ignored.
 
 When the \ref elastic_net_train() \e optimizer argument value is \b 'fista', the \e optimizer_params argument is a string containing name-value pairs with the following format. (Line breaks are inserted for readability.)
 @verbatim
-  'max_stepsize = <value>, 
-   eta = <value>, 
-   warmup = <value>, 
+  'max_stepsize = <value>,
+   eta = <value>,
+   warmup = <value>,
    warmup_lambdas = <value>,
-   warmup_lambda_no = <value>, 
-   warmup_tolerance = <value>, 
+   warmup_lambda_no = <value>,
+   warmup_tolerance = <value>,
    use_active_set = <value>,
-   activeset_tolerance = <value>, 
+   activeset_tolerance = <value>,
    random_stepsize = <value>'
 @endverbatim
 \b Parameters
@@ -199,11 +199,11 @@ When the \ref elastic_net_train() \e optimizer argument value is \b 'igd', the
 the following format. (Line breaks are inserted for readability.)
 @verbatim
   'stepsize = <value>,
-   step_decay = <value>, 
-   threshold = <value>, 
+   step_decay = <value>,
+   threshold = <value>,
    warmup = <value>,
-   warmup_lambdas = <value>, 
-   warmup_lambda_no = <value>, 
+   warmup_lambdas = <value>,
+   warmup_lambda_no = <value>,
    warmup_tolerance = <value>,
    parallel = <value>'
 @endverbatim
@@ -309,17 +309,17 @@ There are several different formats of the prediction function:
 -#
 @code
 elastic_net_gaussian_predict (
-    coefficients, 
-    intercept, 
+    coefficients,
+    intercept,
     ind_var
 ) FROM tbl_result, tbl_new_source LIMIT 10;
 @endcode
 
 -#
 @code
 SELECT madlib.elastic_net_binomial_predict (
-    coefficients, 
-    intercept, 
+    coefficients,
+    intercept,
     ind_var
 ) FROM tbl_result, tbl_new_source LIMIT 10;
 @endcode
@@ -329,8 +329,8 @@ This returns 10 BOOLEAN values.
 -#
 @code
 SELECT madlib.elastic_net_binomial_prob (
-    coefficients, 
-    intercept, 
+    coefficients,
+    intercept,
     ind_var
 ) FROM tbl_result, tbl_new_source LIMIT 10;
 @endcode
@@ -344,7 +344,7 @@ general cross validation function.
 SELECT madlib.elastic_net_predict(
     tbl_model,
     tbl_new_sourcedata,
-    col_id,      
+    col_id,
     tbl_predict)
 @endcode
 \b Arguments
@@ -357,7 +357,7 @@ SELECT madlib.elastic_net_predict(
 <dd>TEXT. The unique ID associated with each row.</dd>
 <dt>tbl_predict</dt>
 <dd>TEXT. The name of table to store the prediction result. </dd>
-</dl> 
+</dl>
 You do not need to specify whether the model is "linear" or "logistic" because this information is already included in the \e tbl_model table.
 
 @anchor examples
@@ -389,19 +389,19 @@ COPY houses FROM STDIN WITH DELIMITER '|';
 @verbatim
 DROP TABLE IF EXISTS houses_en;
 SELECT madlib.elastic_net_train(
-    'houses', 
-    'houses_en', 
-    'price', 
+    'houses',
+    'houses_en',
+    'price',
     'array[tax, bath, size]',
-    'gaussian', 
-    0.5, 
-    0.1, 
-    TRUE, 
-    NULL, 
+    'gaussian',
+    0.5,
+    0.1,
+    TRUE,
+    NULL,
     'fista',
     '',
-    NULL, 
-    10000, 
+    NULL,
+    10000,
     1e-6);
 @endverbatim
 -# View the resulting model.
@@ -413,12 +413,12 @@ SELECT * FROM houses_en;
 -# Use the prediction function to evaluate residuals.
 @verbatim
 SELECT *, price - predict as residual FROM (
-    SELECT 
+    SELECT
         houses.*,
         madlib.elastic_net_predict(
-            'gaussian', 
-            m.coef_nonzero, 
-            m.intercept, 
+            'gaussian',
+            m.coef_all,
+            m.intercept,
             ARRAY[tax,bath,size]
         ) as predict
     FROM houses, houses_en m) s;