I am having an issue with TabularModel which is producing 2 output features where there is only one dependent variable. This is obviously failing while flattening it. Any help is appreciated.
Hello
Could you please provide some more information about your data. Maybe a sample row from your input dataframe, and an example of your independent variable (for ex. what type is it).
3 rows of sample data and 2nd column is the dependent variable. They are either 0 or 1
199759
1
10.5237
4.7965
10.1304
9.3253
9.4114
-4.7457
6.2351
10.8429
-1.4616
9.4703
-2.1009
-4.6201
14.0316
5.7248
7.4399
14.7922
12.3770
-8.5905
9.7220
20.5816
25.1204
7.7466
3.5452
3.2727
4.6172
13.8215
-14.4892
-1.4333
6.1524
6.2017
-0.5184
9.4584
2.8067
22.1086
10.7254
6.9576
1.5358
2.9775
16.1798
-1.1581
-9.4023
6.9065
10.4266
11.6113
5.8958
8.4600
14.2394
-26.9857
16.8233
25.0129
11.2034
4.9862
-8.4792
6.5437
-3.8409
3.2423
18.4656
6.8385
7.2955
9.7975
16.7350
-18.2589
4.7195
3.8674
5.5355
-2.9590
5.1583
9.6265
5.0186
-9.7849
42.8603
0.3008
2.1449
19.3360
16.4567
19.0344
10.5787
18.2526
4.7830
12.9492
2.5682
11.8811
2.3900
1.2092
-8.5651
12.2751
6.5873
9.4599
7.9783
3.5988
-10.4353
7.0910
15.5506
10.6520
11.2937
0.1032
12.1025
34.4568
3.0208
0.2313
4.6557
9.3888
23.6781
1.4542
10.2024
2.6975
9.9136
20.0642
14.0350
14.1472
2.5999
7.0600
3.2345
14.7091
2.4197
-0.2239
2.0687
4.7176
3.5745
-0.6136
3.7944
8.7308
6.3075
-7.2907
3.7128
12.3968
14.2371
1.2334
-5.8172
14.8453
14.2436
0.8166
6.0171
6.7294
-12.0477
2.7692
32.1025
5.1964
-5.7844
-2.8926
4.8620
8.0116
17.3674
11.2760
9.7258
0.8684
8.4282
-12.8874
4.1550
-0.2196
13.0773
12.0120
6.4300
13.6476
9.0520
0.9331
12.1470
-0.1096
3.7800
12.4133
39.8184
5.4111
3.7248
17.5192
-3.1267
9.6603
2.3530
7.7533
6.2000
5.6624
-4.2587
-5.2835
1.1933
4.7467
15.0927
8.2711
2.8916
13.9755
-8.5618
4.1535
8.7149
11.4382
-8.6374
5.8060
3.9588
-0.8331
5.6804
-17.1862
22.9891
-0.0581
13.6381
14.4864
2.3609
-0.8490
18.8579
0.4579
0.6325
7.0770
16.4903
-20.4578
199760
0
8.3461
-3.1356
10.9140
5.0295
14.4948
-6.0191
5.1814
15.6450
-4.2764
7.4871
-4.7391
5.1473
13.8109
8.6541
9.4811
14.6466
10.7758
-0.3142
21.8396
19.3036
18.1135
20.9583
6.7705
4.3217
6.2860
13.2111
-10.5455
-0.5241
5.6200
7.0240
-2.2362
9.2784
1.2067
14.7719
11.2687
4.6927
-0.9582
8.1340
14.4130
-3.9602
-12.7266
11.3982
10.3216
11.2978
11.4086
-5.8340
11.5448
8.3414
-3.0380
24.6373
11.8865
0.6495
0.1393
5.5449
-6.3090
12.5356
18.7714
5.9731
3.7241
8.9240
11.4649
-9.9421
1.8290
3.4680
5.2379
-3.7096
7.6942
18.8967
5.0161
3.4422
18.5819
0.8194
2.1073
32.6567
-5.0406
27.4469
6.1047
19.5315
7.0468
13.9194
13.3114
15.9262
-7.1629
3.7812
5.2883
19.2012
7.4238
2.0110
9.1678
3.7255
-11.2703
6.7968
12.6544
9.7944
7.1502
0.0096
10.4463
14.0702
1.8231
-2.9997
6.0174
14.8245
23.2611
1.7222
10.3610
3.4597
10.7459
10.8883
14.1163
17.3206
7.7394
6.1359
2.2826
2.1927
3.1056
-0.8435
3.2765
24.5159
-10.9072
-0.6803
6.1042
8.7995
-10.2294
4.0570
-0.9538
11.8579
12.7062
-5.3076
2.3931
13.2173
10.3377
0.1286
8.6889
6.2344
-14.4685
2.4922
9.9062
17.2767
10.4170
13.9907
-4.7442
9.4279
9.3616
11.9469
9.5571
9.6445
13.8724
2.2456
4.1596
6.2815
18.2727
10.1354
13.4114
14.9572
-5.1819
-9.3249
13.4090
-4.1721
11.2165
11.1516
26.0916
5.6182
6.0020
9.8993
-0.2080
8.4244
3.2761
-0.8841
5.3507
5.5664
-9.8875
-4.3540
27.8757
2.0015
32.1945
8.9980
-15.6517
11.6968
4.3392
6.2289
-3.1094
11.9303
12.4121
10.4848
-0.6749
-5.3948
4.7786
-28.0623
22.7568
0.6868
-1.2858
7.8473
3.3776
1.7575
10.7121
2.6265
7.0773
10.0061
21.7852
-7.8623
199761
0
10.8498
-6.9508
13.1740
8.0891
12.3278
-2.9784
4.7439
23.5438
-1.2621
7.6835
2.7797
-10.6695
14.1603
9.3403
8.6705
14.3257
10.6320
-14.6474
8.4799
3.4582
14.3815
22.3142
4.4066
2.3600
8.3958
13.2908
-12.1721
1.8667
6.3986
3.4871
-11.9549
9.5673
1.1376
13.6852
11.4322
4.6172
1.5329
5.9929
17.9770
5.6876
-10.1278
11.5141
12.0657
11.2494
12.4778
12.3242
9.9910
-8.6607
23.2893
1.2670
12.0163
11.8079
-3.0246
5.6209
3.8826
4.2991
12.6297
6.5911
5.9098
8.3813
16.2072
-28.3145
1.8893
2.7073
3.1876
1.2894
4.6428
11.2038
5.0318
-0.3100
3.9977
0.3938
-6.6687
30.8452
31.3567
22.9279
-1.7071
15.4288
7.2147
13.0744
-0.3120
8.9416
-4.3711
2.7874
-8.5865
14.4090
-12.5083
11.4882
10.2478
5.6173
-10.7580
6.8355
8.7921
10.6781
6.6052
-0.1883
11.5255
34.1852
2.1394
-0.7372
-3.7996
9.6126
14.9353
1.3596
11.5170
4.0420
12.8756
13.6825
13.9794
14.0735
6.4153
6.5081
4.0648
11.2209
4.8287
2.6320
2.2643
13.7816
2.6461
7.8225
20.2349
13.9471
-4.3976
10.3643
0.6116
12.8611
13.7546
5.2321
-6.3378
14.0503
12.1412
0.7079
6.6173
6.4151
-16.4866
8.4230
9.1862
21.5845
-0.2025
2.3555
2.3826
5.8985
17.6952
12.5947
7.7304
0.8236
13.5120
9.9095
4.0899
20.1796
15.9531
11.6309
6.5661
18.6567
11.2570
-0.0409
14.4745
-1.5392
11.5385
8.9826
17.3912
5.3592
5.1994
4.7310
-3.0477
18.0006
3.2506
-12.5815
7.2778
4.8310
6.4867
-0.6872
16.2197
-12.4416
26.0754
7.2304
3.1712
15.5908
8.2826
-1.3305
-1.5021
8.3902
2.8458
8.4630
-0.8319
-7.4646
8.4976
-40.3805
14.1717
-0.9750
2.8182
4.7460
3.1904
-3.2225
21.4370
-0.5573
6.9020
9.7923
15.5002
-2.8602
If I make changes to .label_from_df(cols=dep_var, label_cls=FloatList, log=True), it gives me 1 out_features but this is an int type and I don’t want to log. I tried setting label_cls to CategoryList but no luck and data.c still gives me 2.
Yes, if you have a categorical dependent variable that can have two values, it’s perfectly normal that your output has two values (which will be the probabilities of being 0 and 1).