Update how-to-configure-auto-train.md

Author: ssalgadodev

articles/machine-learning/how-to-configure-auto-train.md

@@ -221,7 +221,7 @@ Classification | Regression | Time Series Forecasting
 [Xgboost](/python/api/azureml-train-automl-client/azureml.train.automl.constants.supportedmodels.classification#xgboostclassifier----xgboostclassifier-)* |[Xgboost](/python/api/azureml-train-automl-client/azureml.train.automl.constants.supportedmodels.regression#xgboostregressor----xgboostregressor-)* | [Random Forest](https://scikit-learn.org/stable/modules/ensemble.html#random-forests)
 [Naive Bayes](https://scikit-learn.org/stable/modules/naive_bayes.html#bernoulli-naive-bayes)* | [Xgboost](https://xgboost.readthedocs.io/en/latest/parameter.html)  | [ForecastTCN](/python/api/azureml-automl-core/azureml.automl.core.shared.constants.supportedmodels.forecasting#tcnforecaster----tcnforecaster-)
 [Stochastic Gradient Descent (SGD)](/python/api/azureml-train-automl-client/azureml.train.automl.constants.supportedmodels.classification#sgdclassifier----sgd-)* || [Gradient Boosting](https://scikit-learn.org/stable/modules/ensemble.html#regression)
-[Linear SVM Classifier](/python/api/nimbusml/nimbusml.linear_model.linearsvmbinaryclassifier?preserve-view=true&view=nimbusml-py-latest)* || [Stochastic Gradient Descent (SGD)](https://scikit-learn.org/stable/modules/sgd.html#regression)
+ || [Stochastic Gradient Descent (SGD)](https://scikit-learn.org/stable/modules/sgd.html#regression)
 ||| [ExponentialSmoothing](/python/api/azureml-automl-core/azureml.automl.core.shared.constants.supportedmodels.forecasting#exponentialsmoothing----exponentialsmoothing-)
 ||| SeasonalNaive
 ||| Average