from pyspark.ml.classification import NaiveBayes
from pyspark.ml.evaluation import MulticlassClassificationEvaluator

from pyspark.sql import SparkSession

spark= SparkSession\
                .builder \
                .appName("dataFrame") \
                .getOrCreate()


# Load training data
data = spark.read.format("libsvm") \
    .load("/home/luogan/lg/softinstall/spark-2.2.0-bin-hadoop2.7/data/mllib/sample_libsvm_data.txt")

# Split the data into train and test
splits = data.randomSplit([0.6, 0.4], 1234)
train = splits[0]
test = splits[1]

# create the trainer and set its parameters
nb = NaiveBayes(smoothing=1.0, modelType="multinomial")

# train the model
model = nb.fit(train)

# select example rows to display.
predictions = model.transform(test)
predictions.show()

# compute accuracy on the test set
evaluator = MulticlassClassificationEvaluator(labelCol="label", predictionCol="prediction",
                                              metricName="accuracy")
accuracy = evaluator.evaluate(predictions)
print("Test set accuracy = " + str(accuracy))

+-----+--------------------+--------------------+-----------+----------+
|label|            features|       rawPrediction|probability|prediction|
+-----+--------------------+--------------------+-----------+----------+
|  0.0|(692,[95,96,97,12...|[-174115.98587057...|  [1.0,0.0]|       0.0|
|  0.0|(692,[98,99,100,1...|[-178402.52307196...|  [1.0,0.0]|       0.0|
|  0.0|(692,[100,101,102...|[-100905.88974016...|  [1.0,0.0]|       0.0|
|  0.0|(692,[123,124,125...|[-244784.29791241...|  [1.0,0.0]|       0.0|
|  0.0|(692,[123,124,125...|[-196900.88506109...|  [1.0,0.0]|       0.0|
|  0.0|(692,[124,125,126...|[-238164.45338794...|  [1.0,0.0]|       0.0|
|  0.0|(692,[124,125,126...|[-184206.87833381...|  [1.0,0.0]|       0.0|
|  0.0|(692,[127,128,129...|[-214174.52863813...|  [1.0,0.0]|       0.0|
|  0.0|(692,[127,128,129...|[-182844.62193963...|  [1.0,0.0]|       0.0|
|  0.0|(692,[128,129,130...|[-246557.10990301...|  [1.0,0.0]|       0.0|
|  0.0|(692,[152,153,154...|[-208282.08496711...|  [1.0,0.0]|       0.0|
|  0.0|(692,[152,153,154...|[-243457.69885665...|  [1.0,0.0]|       0.0|
|  0.0|(692,[153,154,155...|[-260933.50931276...|  [1.0,0.0]|       0.0|
|  0.0|(692,[154,155,156...|[-220274.72552901...|  [1.0,0.0]|       0.0|
|  0.0|(692,[181,182,183...|[-154830.07125175...|  [1.0,0.0]|       0.0|
|  1.0|(692,[99,100,101,...|[-145978.24563975...|  [0.0,1.0]|       1.0|
|  1.0|(692,[100,101,102...|[-147916.32657832...|  [0.0,1.0]|       1.0|
|  1.0|(692,[123,124,125...|[-139663.27471685...|  [0.0,1.0]|       1.0|
|  1.0|(692,[124,125,126...|[-129013.44238751...|  [0.0,1.0]|       1.0|
|  1.0|(692,[125,126,127...|[-81829.799906049...|  [0.0,1.0]|       1.0|
+-----+--------------------+--------------------+-----------+----------+
only showing top 20 rows

Test set accuracy = 1.0