In this recipe, we use the famous Iris dataset and use Apache Spark API NaiveBayes() to classify/predict which of the three classes of flower a given set of observations belongs to. This is an example of a multi-class classifier and requires multi-class metrics for measurements of fit. The previous recipe used a binary classification and metric to measure the fit.
Naive Bayes machine learning with Spark 2.0 MLlib
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