MultilayerPerceptron creating new classes when only changing features.

Hi, maybe this is meant to happen not sure. sometimes when i add more features or change the alpha 'L2 regularization',  random new classes will be created. I'm assuming that this is happening because the weights are being updated too quickly. I usually only have 2 classes (win, lose). In the example below i add in 3 new features and this results in new classes being made, one with no label and another with the label 0. In the example where the classes are created, the added features are substantially larger than the current features, though would be this way for all samples.
so my question is, is it normal that these new classes are created when changing only features or L2 regularization?
Thanks, Mark
the original features:
(
    [0] => -0.18295004568992
    [1] => -0.83372677429181
    [2] => -0.36064575083765
    [3] => 0.51926591532135
    [4] => -0.72959183673469
    [5] => 0.1991318915626
    [6] => -0.80741699664941
    [7] => -0.14860645750838
    [8] => -0.099870545233018
    [9] => -0.18188394760889
    [10] => -0.38790740176668
    [11] => -0.66406487968322
    [12] => -0.39487511422479
    [13] => -0.60702863234846
    [14] => 1
    [15] => -0.78925525434054
    [16] => -0.090123362777946
    [17] => -0.46497106305209
    [18] => -1
    [19] => 0.072151995126408
    [20] => -0.5138592750533
    [21] => -0.63379530916844
    [22] => -0.78156411818459
    [23] => 0.037884556807799
    [24] => -0.13745050258909
    [25] => -0.13745050258909
    [26] => -0.13745050258909
    [27] => -0.13745050258909
    [28] => -0.13745050258909
    [29] => -0.13745050258909
    [30] => -0.13745050258909
    [31] => -5.2436368202698
    [32] => -0.86024122206422
    [33] => 1.5325879408103
    [34] => 0.65829640938086
    [35] => 0.64121041761968
    [36] => 0.63684030714221
    [37] => 0.62422410521904
    [38] => 0.58765122132457
)

the result of the origional features:
Rubix\ML\Report Object
(
    [attributes:protected] => Array
        (
            [0] => Rubix\ML\Report Object
                (
                    [attributes:protected] => Array
                        (
                            [overall] => Array
                                (
                                    [accuracy] => 0.70227808326787
                                    [balanced accuracy] => 0.70227808326787
                                    [f1 score] => 0.69965350405387
                                    [precision] => 0.70960460647682
                                    [recall] => 0.70227808326787
                                    [specificity] => 0.70227808326787
                                    [negative predictive value] => 0.70960460647682
                                    [false discovery rate] => 0.29039539352318
                                    [miss rate] => 0.29772191673213
                                    [fall out] => 0.29772191673213
                                    [false omission rate] => 0.29039539352318
                                    [mcc] => 0.41181752290182
                                    [informedness] => 0.40455616653574
                                    [markedness] => 0.41920921295364
                                    [true positives] => 3576
                                    [true negatives] => 3576
                                    [false positives] => 1516
                                    [false negatives] => 1516
                                    [cardinality] => 5092
                                )

                            [classes] => Array
                                (
                                    [win] => Array
                                        (
                                            [accuracy] => 0.70227808326787
                                            [balanced accuracy] => 0.70227808326787
                                            [f1 score] => 0.67157712305026
                                            [precision] => 0.7487922705314
                                            [recall] => 0.60879811468971
                                            [specificity] => 0.79575805184603
                                            [negative predictive value] => 0.67041694242224
                                            [false discovery rate] => 0.2512077294686
                                            [miss rate] => 0.39120188531029
                                            [fall out] => 0.20424194815397
                                            [false omission rate] => 0.32958305757776
                                            [informedness] => 0.40455616653574
                                            [markedness] => 0.41920921295364
                                            [mcc] => 0.41181752290182
                                            [true positives] => 1550
                                            [true negatives] => 2026
                                            [false positives] => 520
                                            [false negatives] => 996
                                            [cardinality] => 2546
                                            [proportion] => 0.5
                                        )

                                    [lose] => Array
                                        (
                                            [accuracy] => 0.70227808326787
                                            [balanced accuracy] => 0.70227808326787
                                            [f1 score] => 0.72772988505747
                                            [precision] => 0.67041694242224
                                            [recall] => 0.79575805184603
                                            [specificity] => 0.60879811468971
                                            [negative predictive value] => 0.7487922705314
                                            [false discovery rate] => 0.32958305757776
                                            [miss rate] => 0.20424194815397
                                            [fall out] => 0.39120188531029
                                            [false omission rate] => 0.2512077294686
                                            [informedness] => 0.40455616653574
                                            [markedness] => 0.41920921295364
                                            [mcc] => 0.41181752290182
                                            [true positives] => 2026
                                            [true negatives] => 1550
                                            [false positives] => 996
                                            [false negatives] => 520
                                            [cardinality] => 2546
                                            [proportion] => 0.5
                                        )

                                )

                        )

                )

            [1] => Rubix\ML\Report Object
                (
                    [attributes:protected] => Array
                        (
                            [win] => Array
                                (
                                    [win] => 1550
                                    [lose] => 520
                                )

                            [lose] => Array
                                (
                                    [win] => 996
                                    [lose] => 2026
                                )

                        )

                )

        )

)

next added in 34, 35, 36 to the features array. these values are much higher > 30, so perhaps upset the weights.
(
    [0] => -0.18295004568992
    [1] => -0.83372677429181
    [2] => -0.36064575083765
    [3] => 0.51926591532135
    [4] => -0.72959183673469
    [5] => 0.1991318915626
    [6] => -0.80741699664941
    [7] => -0.14860645750838
    [8] => -0.099870545233018
    [9] => -0.18188394760889
    [10] => -0.38790740176668
    [11] => -0.66406487968322
    [12] => -0.39487511422479
    [13] => -0.60702863234846
    [14] => 1
    [15] => -0.78925525434054
    [16] => -0.090123362777946
    [17] => -0.46497106305209
    [18] => -1
    [19] => 0.072151995126408
    [20] => -0.5138592750533
    [21] => -0.63379530916844
    [22] => -0.78156411818459
    [23] => 0.037884556807799
    [24] => -0.13745050258909
    [25] => -0.13745050258909
    [26] => -0.13745050258909
    [27] => -0.13745050258909
    [28] => -0.13745050258909
    [29] => -0.13745050258909
    [30] => -0.13745050258909
    [31] => -5.2436368202698
    [32] => -0.86024122206422
    [33] => 1.5325879408103
    [34] => 40.947888842454
    [35] => 15.049572702343
    [36] => 28.375953124697
    [37] => 0.65829640938086
    [38] => 0.64121041761968
    [39] => 0.63684030714221
    [40] => 0.62422410521904
    [41] => 0.58765122132457
)

This Results in the following. Here there are now 4 classes.
Rubix\ML\Report Object
(
    [attributes:protected] => Array
        (
            [0] => Rubix\ML\Report Object
                (
                    [attributes:protected] => Array
                        (
                            [overall] => Array
                                (
                                    [accuracy] => 0.42873043933739
                                    [balanced accuracy] => 0.42873045587902
                                    [f1 score] => 0.40974282541048
                                    [precision] => 0.46890839533503
                                    [recall] => 0.42864624247185
                                    [specificity] => 0.42881466928618
                                    [negative predictive value] => 0.46862462572938
                                    [false discovery rate] => 0.53109160466497
                                    [miss rate] => 0.57135375752815
                                    [fall out] => 0.57118533071382
                                    [false omission rate] => 0.53137537427062
                                    [mcc] => 0.22733178488711
                                    [informedness] => -0.14253908824197
                                    [markedness] => -0.062466978935593
                                    [true positives] => 3274
                                    [true negatives] => 3274
                                    [false positives] => 1816
                                    [false negatives] => 1818
                                    [cardinality] => 5092
                                )

                            [classes] => Array
                                (
                                    [win] => Array
                                        (
                                            [accuracy] => 0.64309565900609
                                            [balanced accuracy] => 0.64314908242368
                                            [f1 score] => 0.5098462368492
                                            [precision] => 0.81395348837209
                                            [recall] => 0.37117046347211
                                            [specificity] => 0.91512770137525
                                            [negative predictive value] => 0.59262086513995
                                            [false discovery rate] => 0.18604651162791
                                            [miss rate] => 0.62882953652789
                                            [fall out] => 0.084872298624754
                                            [false omission rate] => 0.40737913486005
                                            [informedness] => 0.28629816484736
                                            [markedness] => 0.40657435351204
                                            [mcc] => 0.34117662769378
                                            [true positives] => 945
                                            [true negatives] => 2329
                                            [false positives] => 216
                                            [false negatives] => 1601
                                            [cardinality] => 2546
                                            [proportion] => 0.5
                                        )

                                    [lose] => Array
                                        (
                                            [accuracy] => 0.64309565900609
                                            [balanced accuracy] => 0.64304228521337
                                            [f1 score] => 0.71938223938224
                                            [precision] => 0.59277169763299
                                            [recall] => 0.91476826394344
                                            [specificity] => 0.3713163064833
                                            [negative predictive value] => 0.81325301204819
                                            [false discovery rate] => 0.40722830236701
                                            [miss rate] => 0.085231736056559
                                            [fall out] => 0.6286836935167
                                            [false omission rate] => 0.18674698795181
                                            [informedness] => 0.28608457042674
                                            [markedness] => 0.40602470968118
                                            [mcc] => 0.34081872696755
                                            [true positives] => 2329
                                            [true negatives] => 945
                                            [false positives] => 1600
                                            [false negatives] => 217
                                            [cardinality] => 2546
                                            [proportion] => 0.5
                                        )

                                    [] => Array
                                        (
                                            [accuracy] => 0
                                            [balanced accuracy] => 0
                                            [f1 score] => 0
                                            [precision] => 0
                                            [recall] => 0
                                            [specificity] => 0
                                            [negative predictive value] => 0
                                            [false discovery rate] => 1
                                            [miss rate] => 1
                                            [fall out] => 1
                                            [false omission rate] => 1
                                            [informedness] => -1
                                            [markedness] => -1
                                            [mcc] => 0
                                            [true positives] => 0
                                            [true negatives] => 0
                                            [false positives] => 0
                                            [false negatives] => 0
                                            [cardinality] => 0
                                            [proportion] => 0
                                        )

                                )

                        )

                )

            [1] => Rubix\ML\Report Object
                (
                    [attributes:protected] => Array
                        (
                            [win] => Array
                                (
                                    [win] => 945
                                    [lose] => 216
                                    [] => 0
                                )

                            [lose] => Array
                                (
                                    [win] => 1600
                                    [lose] => 2329
                                    [] => 0
                                )

                            [] => Array
                                (
                                    [win] => 0
                                    [lose] => 0
                                    [] => 0
                                )

                            [0] => Array
                                (
                                    [win] => 1
                                    [lose] => 1
                                )

                        )

                )

        )

)

here is my model:
[2022-02-13 17:46:17] INFO: Multilayer Perceptron (hidden layers: [0: Dense (neurons: 39, alpha: 1.0E-5, bias: true, weight initializer: He, bias initializer: Constant (value: 0)), 1: Activation (activation fn: ELU (alpha: 2.5)), 2: Batch Norm (decay: 0.3, beta initializer: Constant (value: 0), gamma initializer: Normal (std_dev: 1)), 3: Dense (neurons: 39, alpha: 1.0E-5, bias: true, weight initializer: He, bias initializer: Constant (value: 0)), 4: Activation (activation fn: ELU (alpha: 2.5)), 5: Batch Norm (decay: 0.3, beta initializer: Constant (value: 0), gamma initializer: Normal (std_dev: 1)), 6: Dense (neurons: 39, alpha: 1.0E-5, bias: true, weight initializer: He, bias initializer: Constant (value: 0)), 7: PReLU (initializer: Normal (std_dev: 0.25))], batch size: 128, optimizer: AdaMax (rate: 0.0001, momentum_decay: 0.02, norm_decay: 0.999), alpha: 0.0001, epochs: 20, min change: 1.0E-8, window: 20, hold out: 0, cost fn: Cross Entropy, metric: MCC)
versions:
rubix/ml                         1.3.1
rubix/tensor                     3.0.1

Hey, great thanks, i'll check out that scaling transformer.
This is the description of the training data. here some of the min/max values are really big, so i guess that's creating a problem:
Rubix\ML\Report Object
(
    [attributes:protected] => Array
        (
            [0] => Array
                (
                    [offset] => 0
                    [type] => continuous
                    [mean] => 0.073158336241229
                    [standard deviation] => 0.59278752022008
                    [skewness] => 0.18050459206108
                    [kurtosis] => -1.1060024598621
                    [min] => -1
                    [25%] => -0.40437259494097
                    [median] => -0.010743115488011
                    [75%] => 0.56462256866081
                    [max] => 1
                )

            [1] => Array
                (
                    [offset] => 1
                    [type] => continuous
                    [mean] => 0.072887712820359
                    [standard deviation] => 0.59274961805198
                    [skewness] => 0.18182032626333
                    [kurtosis] => -1.108444696689
                    [min] => -1
                    [25%] => -0.40518174207871
                    [median] => -0.013052036343245
                    [75%] => 0.56438053156084
                    [max] => 1
                )

            [2] => Array
                (
                    [offset] => 2
                    [type] => continuous
                    [mean] => 0.076486215303728
                    [standard deviation] => 0.58949103578917
                    [skewness] => 0.18456694691724
                    [kurtosis] => -1.1130568082275
                    [min] => -1
                    [25%] => -0.40241150201391
                    [median] => -0.0076349423685047
                    [75%] => 0.56632698064078
                    [max] => 1
                )

            [3] => Array
                (
                    [offset] => 3
                    [type] => continuous
                    [mean] => 0.074519155189057
                    [standard deviation] => 0.59143782762688
                    [skewness] => 0.18520002003572
                    [kurtosis] => -1.1111623693135
                    [min] => -1
                    [25%] => -0.40317957628131
                    [median] => -0.010463522596028
                    [75%] => 0.56553091187756
                    [max] => 1
                )

            [4] => Array
                (
                    [offset] => 4
                    [type] => continuous
                    [mean] => 0.074125991698316
                    [standard deviation] => 0.58934816356009
                    [skewness] => 0.19032267601938
                    [kurtosis] => -1.1077754868988
                    [min] => -1
                    [25%] => -0.40306057345846
                    [median] => -0.011357426720759
                    [75%] => 0.56169735639559
                    [max] => 1
                )

            [5] => Array
                (
                    [offset] => 5
                    [type] => continuous
                    [mean] => 0.07563656228373
                    [standard deviation] => 0.58736708642607
                    [skewness] => 0.19147678613828
                    [kurtosis] => -1.1026457857705
                    [min] => -1
                    [25%] => -0.40002777663832
                    [median] => -0.009106152090924
                    [75%] => 0.55933070764148
                    [max] => 1
                )

            [6] => Array
                (
                    [offset] => 6
                    [type] => continuous
                    [mean] => 0.075097019737031
                    [standard deviation] => 0.58763086813308
                    [skewness] => 0.19098448629755
                    [kurtosis] => -1.1034697476034
                    [min] => -1
                    [25%] => -0.40057109091926
                    [median] => -0.0088976455533206
                    [75%] => 0.56020068186145
                    [max] => 1
                )

            [7] => Array
                (
                    [offset] => 7
                    [type] => continuous
                    [mean] => 0.074173307011829
                    [standard deviation] => 0.58783674511298
                    [skewness] => 0.19150741440264
                    [kurtosis] => -1.1006862794473
                    [min] => -1
                    [25%] => -0.40171625011792
                    [median] => -0.0109137686648
                    [75%] => 0.55921851727334
                    [max] => 1
                )

            [8] => Array
                (
                    [offset] => 8
                    [type] => continuous
                    [mean] => -0.026850110890546
                    [standard deviation] => 0.77348242417533
                    [skewness] => 0.075390230356457
                    [kurtosis] => -1.5629839350193
                    [min] => -1
                    [25%] => -0.83943191743022
                    [median] => -0.06085617559787
                    [75%] => 0.80484782387103
                    [max] => 1
                )

            [9] => Array
                (
                    [offset] => 9
                    [type] => continuous
                    [mean] => -0.11109153767878
                    [standard deviation] => 0.66579899668259
                    [skewness] => 0.23176240313133
                    [kurtosis] => -1.2707062919653
                    [min] => -1
                    [25%] => -0.73093710006024
                    [median] => -0.17556707764978
                    [75%] => 0.46238225582278
                    [max] => 1
                )

            [10] => Array
                (
                    [offset] => 10
                    [type] => continuous
                    [mean] => -0.14446830099695
                    [standard deviation] => 0.61837604484296
                    [skewness] => 0.35399030090261
                    [kurtosis] => -1.0177645256259
                    [min] => -1
                    [25%] => -0.67438132227174
                    [median] => -0.22450307489692
                    [75%] => 0.33241647592402
                    [max] => 1
                )

            [11] => Array
                (
                    [offset] => 11
                    [type] => continuous
                    [mean] => -0.16840792106228
                    [standard deviation] => 0.5923320227946
                    [skewness] => 0.40780665107476
                    [kurtosis] => -0.85709703531617
                    [min] => -1
                    [25%] => -0.65912199187375
                    [median] => -0.24576309223928
                    [75%] => 0.25919308316194
                    [max] => 1
                )

            [12] => Array
                (
                    [offset] => 12
                    [type] => continuous
                    [mean] => -0.18141398104781
                    [standard deviation] => 0.57862273983947
                    [skewness] => 0.41879698481403
                    [kurtosis] => -0.78759807809372
                    [min] => -1
                    [25%] => -0.65989082831402
                    [median] => -0.24951124863536
                    [75%] => 0.2273941402201
                    [max] => 1
                )

            [13] => Array
                (
                    [offset] => 13
                    [type] => continuous
                    [mean] => -0.17961244661334
                    [standard deviation] => 0.58507725312153
                    [skewness] => 0.39951608788894
                    [kurtosis] => -0.84723770695581
                    [min] => -1
                    [25%] => -0.6750838601884
                    [median] => -0.24565067548312
                    [75%] => 0.23980314876669
                    [max] => 1
                )

            [14] => Array
                (
                    [offset] => 14
                    [type] => continuous
                    [mean] => -0.18499667683254
                    [standard deviation] => 0.601457334065
                    [skewness] => 0.38846238819523
                    [kurtosis] => -0.94078857819941
                    [min] => -1
                    [25%] => -0.7053644961375
                    [median] => -0.26113543404189
                    [75%] => 0.27176743931142
                    [max] => 1
                )

            [15] => Array
                (
                    [offset] => 15
                    [type] => continuous
                    [mean] => -0.16489101636419
                    [standard deviation] => 0.6350170590341
                    [skewness] => 0.33066137351541
                    [kurtosis] => -1.1352779060633
                    [min] => -1
                    [25%] => -0.7440459523763
                    [median] => -0.24525462195734
                    [75%] => 0.35262245494872
                    [max] => 1
                )

            [16] => Array
                (
                    [offset] => 16
                    [type] => continuous
                    [mean] => -0.14381375426929
                    [standard deviation] => 0.68495444453427
                    [skewness] => 0.2831685389879
                    [kurtosis] => -1.3183993735176
                    [min] => -1
                    [25%] => -0.80575797274956
                    [median] => -0.24041950029283
                    [75%] => 0.46691341669247
                    [max] => 1
                )

            [17] => Array
                (
                    [offset] => 17
                    [type] => continuous
                    [mean] => -0.12298396872957
                    [standard deviation] => 0.7589842740407
                    [skewness] => 0.26501788981002
                    [kurtosis] => -1.4775590187994
                    [min] => -1
                    [25%] => -0.90677150337106
                    [median] => -0.25581395348837
                    [75%] => 0.6317964437051
                    [max] => 1
                )

            [18] => Array
                (
                    [offset] => 18
                    [type] => continuous
                    [mean] => 10.016284105674
                    [standard deviation] => 5.6837465805299
                    [skewness] => 2.7357687757698
                    [kurtosis] => 24.321122533369
                    [min] => 1.0E-8
                    [25%] => 6
                    [median] => 9
                    [75%] => 12
                    [max] => 141
                )

            [19] => Array
                (
                    [offset] => 19
                    [type] => continuous
                    [mean] => 20.091598094423
                    [standard deviation] => 8.5359791101318
                    [skewness] => 3.3305018479522
                    [kurtosis] => 35.567813634199
                    [min] => 1.0E-8
                    [25%] => 14
                    [median] => 18
                    [75%] => 24
                    [max] => 168
                )

            [20] => Array
                (
                    [offset] => 20
                    [type] => continuous
                    [mean] => 30.098007795607
                    [standard deviation] => 10.646733412916
                    [skewness] => 3.2078673443585
                    [kurtosis] => 31.719868335951
                    [min] => 1.0E-8
                    [25%] => 23
                    [median] => 28
                    [75%] => 35
                    [max] => 188
                )

            [21] => Array
                (
                    [offset] => 21
                    [type] => continuous
                    [mean] => 40.050498051187
                    [standard deviation] => 12.139482986044
                    [skewness] => 2.5715532250001
                    [kurtosis] => 21.355046072269
                    [min] => 1.0E-8
                    [25%] => 32
                    [median] => 38
                    [75%] => 46
                    [max] => 195
                )

            [22] => Array
                (
                    [offset] => 22
                    [type] => continuous
                    [mean] => 49.892334374536
                    [standard deviation] => 13.255996743164
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                    [25%] => 41
                    [median] => 48
                    [75%] => 57
                    [max] => 195
                )

            [23] => Array
                (
                    [offset] => 23
                    [type] => continuous
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                    [max] => 144
                )

            [24] => Array
                (
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            [26] => Array
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                )

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                (
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                )

            [28] => Array
                (
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                )

            [29] => Array
                (
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                    [type] => continuous
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                )

            [30] => Array
                (
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            [31] => Array
                (
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                (
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                (
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                    [median] => 34.031359659348
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                    [max] => 100
                )

            [34] => Array
                (
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                    [type] => continuous
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                    [median] => 0.89028736315043
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                )

            [35] => Array
                (
                    [offset] => 35
                    [type] => continuous
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                    [median] => 0.88836833796511
                    [75%] => 0.94692337550665
                    [max] => 1
                )

            [36] => Array
                (
                    [offset] => 36
                    [type] => continuous
                    [mean] => 0.75884709803968
                    [standard deviation] => 0.33617566031173
                    [skewness] => -2.7198264296161
                    [kurtosis] => 8.0122872889507
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                    [median] => 0.88613345653264
                    [75%] => 0.945291377991
                    [max] => 1
                )

            [37] => Array
                (
                    [offset] => 37
                    [type] => continuous
                    [mean] => 0.75802027779007
                    [standard deviation] => 0.33443604926285
                    [skewness] => -2.7038026135237
                    [kurtosis] => 7.910577585936
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                    [median] => 0.88467619651903
                    [75%] => 0.9444219349168
                    [max] => 1
                )

            [38] => Array
                (
                    [offset] => 38
                    [type] => continuous
                    [mean] => 0.75724122095796
                    [standard deviation] => 0.3336427309714
                    [skewness] => -2.696263623649
                    [kurtosis] => 7.8668853299441
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                    [median] => 0.88356943671922
                    [75%] => 0.94352153462547
                    [max] => 1
                )

            [39] => Array
                (
                    [offset] => 39
                    [type] => categorical
                    [num categories] => 2
                    [probabilities] => Array
                        (
                            [lose] => 0.5
                            [win] => 0.5
                        )

                )

        )

)

here is the description of the testing dataset. Same thing with the large min/max.
Rubix\ML\Report Object
(
    [attributes:protected] => Array
        (
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                (
                    [offset] => 0
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                    [median] => 0.048818467316023
                    [75%] => 0.63257002750708
                    [max] => 1
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            [1] => Array
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                    [median] => 0.046390395297782
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                    [max] => 1
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            [2] => Array
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                    [max] => 1
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            [3] => Array
                (
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                    [standard deviation] => 0.58388359302166
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                    [kurtosis] => -1.1698507839965
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                    [median] => 0.048648005718833
                    [75%] => 0.63067723746301
                    [max] => 1
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            [4] => Array
                (
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                    [type] => continuous
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                    [median] => 0.047794028916663
                    [75%] => 0.62662891631448
                    [max] => 1
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            [5] => Array
                (
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                    [75%] => 0.62818568128745
                    [max] => 1
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                (
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                (
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                    [max] => 1
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            [10] => Array
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                    [max] => 1
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            [11] => Array
                (
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                    [median] => -0.30854733205743
                    [75%] => 0.15459599432181
                    [max] => 1
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            [12] => Array
                (
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                    [max] => 1
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                (
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                    [type] => continuous
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                (
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                    [75%] => 0.30922995635085
                    [max] => 1
                )

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                (
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                    [type] => continuous
                    [mean] => -0.15108679192773
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            [16] => Array
                (
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                    [type] => continuous
                    [mean] => -0.11968868560352
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                    [skewness] => 0.2275043586754
                    [kurtosis] => -1.3516275315534
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                    [75%] => 0.49494478156521
                    [max] => 1
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            [17] => Array
                (
                    [offset] => 17
                    [type] => continuous
                    [mean] => -0.084742545472565
                    [standard deviation] => 0.76906198409391
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                    [kurtosis] => -1.5339992211115
                    [min] => -1
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                    [median] => -0.21520002023908
                    [75%] => 0.73143663239437
                    [max] => 1
                )

            [18] => Array
                (
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                    [type] => continuous
                    [mean] => 9.9003489724719
                    [standard deviation] => 6.423812744527
                    [skewness] => 7.9369229190317
                    [kurtosis] =><PHONE_NUMBER>5653
                    [min] => 1.0E-8
                    [25%] => 6
                    [median] => 9
                    [75%] => 12
                    [max] => 183
                )

            [19] => Array
                (
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                    [type] => continuous
                    [mean] => 19.943582784802
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                    [skewness] => 4.5961747921423
                    [kurtosis] => 53.891228883765
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                    [25%] => 14
                    [median] => 18
                    [75%] => 24
                    [max] => 175
                )

            [20] => Array
                (
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                    [type] => continuous
                    [mean] => 30.109344708028
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                    [min] => 1.0E-8
                    [25%] => 23
                    [median] => 28
                    [75%] => 35
                    [max] => 190
                )

            [21] => Array
                (
                    [offset] => 21
                    [type] => continuous
                    [mean] => 39.999418398113
                    [standard deviation] => 13.310260923173
                    [skewness] => 3.6575761919551
                    [kurtosis] => 32.095715013751
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                    [25%] => 32
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                    [75%] => 46
                    [max] => 194
                )

            [22] => Array
                (
                    [offset] => 22
                    [type] => continuous
                    [mean] => 49.724893388816
                    [standard deviation] => 14.398772982294
                    [skewness] => 2.3885012765667
                    [kurtosis] => 17.362537206798
                    [min] => 1.0E-8
                    [25%] => 41
                    [median] => 48
                    [75%] => 56.75
                    [max] => 195
                )

            [23] => Array
                (
                    [offset] => 23
                    [type] => continuous
                    [mean] => 10.622528111673
                    [standard deviation] => 9.0526663570682
                    [skewness] => 9.9724368750061
                    [kurtosis] =><PHONE_NUMBER>1501
                    [min] => 1.0E-8
                    [25%] => 6
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                    [75%] => 13
                    [max] => 194
                )

            [24] => Array
                (
                    [offset] => 24
                    [type] => continuous
                    [mean] => 20.879216750741
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                    [skewness] => 3.4705788857538
                    [kurtosis] => 23.558804981748
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                    [25%] => 14
                    [median] => 19
                    [75%] => 25
                    [max] => 147
                )

            [25] => Array
                (
                    [offset] => 25
                    [type] => continuous
                    [mean] => 31.265219079248
                    [standard deviation] => 12.623543644129
                    [skewness] => 2.8291333686977
                    [kurtosis] => 16.640181784757
                    [min] => 1.0E-11
                    [25%] => 23.25
                    [median] => 29
                    [75%] => 36
                    [max] => 157
                )

            [26] => Array
                (
                    [offset] => 26
                    [type] => continuous
                    [mean] => 41.635517644584
                    [standard deviation] => 14.875278123059
                    [skewness] => 2.4628861202357
                    [kurtosis] => 12.637209441448
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                    [25%] => 32
                    [median] => 39
                    [75%] => 47
                    [max] => 177
                )

            [27] => Array
                (
                    [offset] => 27
                    [type] => continuous
                    [mean] => 51.800116326408
                    [standard deviation] => 16.339475642578
                    [skewness] => 1.9356894376702
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                    [min] => 1.0E-11
                    [25%] => 42
                    [median] => 49
                    [75%] => 59
                    [max] => 192
                )

            [28] => Array
                (
                    [offset] => 28
                    [type] => continuous
                    [mean] => -12.590552220905
                    [standard deviation] =><PHONE_NUMBER>2596
                    [skewness] => -44.977932477856
                    [kurtosis] => 2110.5965159998
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                    [25%] => -7.9201126400017
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                    [75%] => 2.5548857571216
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                )

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                (
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                    [type] => continuous
                    [mean] => -3.1558775105164
                    [standard deviation] =><PHONE_NUMBER>7458
                    [skewness] => -62.521597631184
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                    [75%] => 2.7820544021378
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                )

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                (
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                    [mean] => 0.14511626605148
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                    [skewness] => -68.989214980257
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                    [75%] => 2.1652657316866
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                )

            [31] => Array
                (
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            [32] => Array
                (
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                    [type] => continuous
                    [mean] => 28.621936356442
                    [standard deviation] => 25.147520221035
                    [skewness] => 0.88153815776743
                    [kurtosis] => -0.18104664446397
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                    [25%] => 7.3204172247982
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                    [75%] => 44.936006353526
                    [max] => 100
                )

            [33] => Array
                (
                    [offset] => 33
                    [type] => continuous
                    [mean] => 34.494940218899
                    [standard deviation] => 26.524100429816
                    [skewness] => 0.58881607635933
                    [kurtosis] => -0.71819398260898
                    [min] => 0
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                    [max] => 100
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            [34] => Array
                (
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                    [mean] => 0.77741684098507
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                    [skewness] => -2.9123410356797
                    [kurtosis] => 9.891816253491
                    [min] => -1
                    [25%] => 0.75256834147617
                    [median] => 0.89297911813324
                    [75%] => 0.95041417881894
                    [max] => 1
                )

            [35] => Array
                (
                    [offset] => 35
                    [type] => continuous
                    [mean] => 0.77607334452162
                    [standard deviation] => 0.31368448733586
                    [skewness] => -2.8668091947568
                    [kurtosis] => 9.4756426091357
                    [min] => -1
                    [25%] => 0.75106479505886
                    [median] => 0.89156676103273
                    [75%] => 0.94869301913728
                    [max] => 1
                )

            [36] => Array
                (
                    [offset] => 36
                    [type] => continuous
                    [mean] => 0.77477839588871
                    [standard deviation] => 0.31149906200191
                    [skewness] => -2.8170322080284
                    [kurtosis] => 9.0433381244472
                    [min] => -1
                    [25%] => 0.75101706585277
                    [median] => 0.89078059494632
                    [75%] => 0.9459795027421
                    [max] => 1
                )

            [37] => Array
                (
                    [offset] => 37
                    [type] => continuous
                    [mean] => 0.77340738690127
                    [standard deviation] => 0.30953509557455
                    [skewness] => -2.7864730660301
                    [kurtosis] => 8.8334646112434
                    [min] => -1
                    [25%] => 0.74971959855052
                    [median] => 0.88872572516883
                    [75%] => 0.94445985673072
                    [max] => 1
                )

            [38] => Array
                (
                    [offset] => 38
                    [type] => continuous
                    [mean] => 0.77257737130506
                    [standard deviation] => 0.30754970226268
                    [skewness] => -2.7622035399736
                    [kurtosis] => 8.6733758543893
                    [min] => -1
                    [25%] => 0.74937009629357
                    [median] => 0.88647977051344
                    [75%] => 0.94371054054496
                    [max] => 1
                )

            [39] => Array
                (
                    [offset] => 39
                    [type] => categorical
                    [num categories] => 2
                    [probabilities] => Array
                        (
                            [lose] => 0.5
                            [win] => 0.5
                        )

                )

        )

)

Okay here are the predictions. All are empty.
Array
(
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