Major Description
I believe I have discovered a bug when loading MultilayerPerceptronClassificationModel in spark 3.0.0, scala 2.1.2 which I have tested and can see is not there in at least Spark 2.4.3, Scala 2.11. (I'm not sure if the Scala version is important).
I am using pyspark on a databricks cluster and importing the library "from pyspark.ml.classification import MultilayerPerceptronClassificationModel"
When running model=MultilayerPerceptronClassificationModel.("load") and then model. transform (df) I get the following error: IllegalArgumentException: MultilayerPerceptronClassifier_8055d1368e78 parameter solver given invalid value auto.
This issue can be easily replicated by running the example given on the spark documents: http://spark.apache.org/docs/latest/ml-classification-regression.html#multilayer-perceptron-classifier
Then adding a save model, load model and transform statement as such:
from pyspark.ml.classification import MultilayerPerceptronClassifier
from pyspark.ml.evaluation import MulticlassClassificationEvaluator
# Load training data
data = spark.read.format("libsvm")\
.load("data/mllib/sample_multiclass_classification_data.txt")
# Split the data into train and test
splits = data.randomSplit([0.6, 0.4], 1234)
train = splits[0]
test = splits[1]
# specify layers for the neural network:
# input layer of size 4 (features), two intermediate of size 5 and 4
# and output of size 3 (classes)
layers = [4, 5, 4, 3]
# create the trainer and set its parameters
trainer = MultilayerPerceptronClassifier(maxIter=100, layers=layers, blockSize=128, seed=1234)
# train the model
model = trainer.fit(train)
# compute accuracy on the test set
result = model.transform(test)
predictionAndLabels = result.select("prediction", "label")
evaluator = MulticlassClassificationEvaluator(metricName="accuracy")
print("Test set accuracy = " + str(evaluator.evaluate(predictionAndLabels)))
from pyspark.ml.classification import MultilayerPerceptronClassifier, MultilayerPerceptronClassificationModel
model.save(Save_location)
model2. MultilayerPerceptronClassificationModel.load(Save_location)
result_from_loaded = model2.transform(test)
