Spark MLLib LogisticRegression debug model?
<p>I'm working on a LogisticRegression model and trying to debug.</p>

<p>It's a simple thing but can't seem to get it to work: just have <code>time of day</code> and a <code>state 0 or 1</code>, and want to predict the state for a given time of day.</p>

<p>There are no errors when training the model, but I see this:
<code>GradientDescent: GradientDescent.runMiniBatchSGD finished. Last 10 stochastic losses NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN</code> </p>

<p>in the logs
when trying to <code>eval</code> I always end up with an error <code>java.util.NoSuchElementException: key not found: keyname</code></p>

<p>I have seen this before when feeding the classifier a feature set that is not possible, but here I am only using 1 feature and it's a simple model, so I don't understand what is wrong. </p>

<p>Any idea how I can see what is going on?</p>

<p>I also used <code>BinaryClassificationMetrics</code> and it returns </p>

<p><code>FmeasureCurve</code> = <code>(NaN,0.17630133869823753)</code></p>

<p><code>ROCCurve</code> = </p>

<p><code>(0.0,0.0)
(1.0,1.0)
(1.0,1.0)</code></p>

<p>How would I print the model information to see what values are in there?
I there an easy way to get this data?</p>

<p>When I print the model I only get: 
<code>org.apache.spark.mllib.classification.LogisticRegressionModel: intercept = 0.0, numFeatures = 1, numClasses = 2, threshold = None</code></p>

<p>Thanks</p>