Start to fix script.

Author: rhall

bin/demo.sh

@@ -3,6 +3,6 @@
 # - make monolithic conjecture jar.
 sbt clean assembly
 # - make the instances.
-java -cp target/conjecture-assembly-0.0.7-SNAPSHOT.jar com.twitter.scalding.Tool com.etsy.conjecture.demo.IrisDataToMulticlassLabeledInstances --input_file data/iris.tsv --output_file iris_model/instances --local
+java -cp target/conjecture-assembly-*.jar com.twitter.scalding.Tool com.etsy.conjecture.demo.IrisDataToMulticlassLabeledInstances --input_file data/iris.tsv --output_file iris_model/instances --local
 # - construct the classifier.
-java -cp target/conjecture-assembly-0.0.7-SNAPSHOT.jar com.twitter.scalding.Tool com.etsy.conjecture.demo.LearnMulticlassClassifier --input iris_model/instances --output iris_model --class_names Iris-versicolor,Iris-virginica,Iris-setosa --iters 5 --folds 3 --local
+java -cp target/conjecture-assembly-*.jar com.twitter.scalding.Tool com.etsy.conjecture.demo.LearnMulticlassClassifier --input iris_model/instances --output iris_model --class_names Iris-versicolor,Iris-virginica,Iris-setosa --iters 5 --folds 3 --local

src/main/java/com/etsy/conjecture/model/SGDOptimizer.java

@@ -146,15 +146,15 @@ public SGDOptimizer<L> setExponentialLearningRateBase(double base) {
 
     public SGDOptimizer<L> setGaussianRegularizationWeight(double gaussian) {
         checkArgument(gaussian >= 0.0,
-                "gaussian regularization weight must be positive, given: %f",
+                "gaussian regularization weight must be non-negative, given: %f",
                 gaussian);
         this.gaussian = gaussian;
         return this;
     }
 
     public SGDOptimizer<L> setLaplaceRegularizationWeight(double laplace) {
         checkArgument(laplace >= 0.0,
-                "laplace regularization weight must be positive, given: %f",
+                "laplace regularization weight must be non-negative, given: %f",
                 laplace);
         this.laplace = laplace;
         return this;