BasicCSVClassifier does not classify at all

#### Issue Description

Running BasicCSVClassifier results in a bad classifcation stats:

```
o.n.l.f.Nd4jBackend - Loaded [CpuBackend] backend
o.n.n.NativeOpsHolder - Number of threads used for linear algebra: 4
o.n.l.c.n.CpuNDArrayFactory - *********************************** CPU Feature Check Warning ***********************************
o.n.l.c.n.CpuNDArrayFactory - Warning: Initializing ND4J with Generic x86 binary on a CPU with AVX/AVX2 support
o.n.l.c.n.CpuNDArrayFactory - Using ND4J with AVX/AVX2 will improve performance. See deeplearning4j.org/cpu for more details
o.n.l.c.n.CpuNDArrayFactory - Or set environment variable ND4J_IGNORE_AVX=true to suppress this warning
o.n.l.c.n.CpuNDArrayFactory - *************************************************************************************************
o.n.n.Nd4jBlas - Number of threads used for OpenMP BLAS: 4
o.n.l.a.o.e.DefaultOpExecutioner - Backend used: [CPU]; OS: [Windows 10]
o.n.l.a.o.e.DefaultOpExecutioner - Cores: [8]; Memory: [14,2GB];
o.n.l.a.o.e.DefaultOpExecutioner - Blas vendor: [OPENBLAS]
o.d.e.d.BasicCSVClassifier - Build model....
o.d.n.m.MultiLayerNetwork - Starting MultiLayerNetwork with WorkspaceModes set to [training: ENABLED; inference: ENABLED], cacheMode set to [NONE]
o.d.o.l.ScoreIterationListener - Score at iteration 0 is 1.2347359410511736
o.d.o.l.ScoreIterationListener - Score at iteration 100 is 0.1004844711532599
o.d.o.l.ScoreIterationListener - Score at iteration 200 is 0.039669264507044
o.d.o.l.ScoreIterationListener - Score at iteration 300 is 0.024435827880011744
o.d.o.l.ScoreIterationListener - Score at iteration 400 is 0.017831637223516515
o.d.o.l.ScoreIterationListener - Score at iteration 500 is 0.014205604188074546
o.d.o.l.ScoreIterationListener - Score at iteration 600 is 0.011934892657567751
o.d.o.l.ScoreIterationListener - Score at iteration 700 is 0.010388604478515275
o.d.o.l.ScoreIterationListener - Score at iteration 800 is 0.009272695178875455
o.d.o.l.ScoreIterationListener - Score at iteration 900 is 0.00843236932311402
o.d.e.d.BasicCSVClassifier -

========================Evaluation Metrics========================
# of classes: 3
Accuracy: 0,1818
Precision: 0,3333
Recall: 0,1818 (2 classes excluded from average)
F1 Score: 0,3077 (2 classes excluded from average)
Precision, recall & F1: macro-averaged (equally weighted avg. of 3 classes)

Warning: 2 classes were never predicted by the model and were excluded from average recall
Classes excluded from average recall: [1, 2]

=========================Confusion Matrix=========================
0 1 2
----------
8 13 23 | 0 = 0
0 0 0 | 1 = 1
0 0 0 | 2 = 2

Confusion matrix format: Actual (rowClass) predicted as (columnClass) N times
==================================================================
```

#### Version Information

* 1.0.0-beta6
* WIN10

#### Question
Is it a configuration error in any form? Or is the example just not working with the newest version?