-
Notifications
You must be signed in to change notification settings - Fork 9
/
Copy pathC2W2.ipynb
1191 lines (1191 loc) · 387 KB
/
C2W2.ipynb
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
821
822
823
824
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
842
843
844
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
860
861
862
863
864
865
866
867
868
869
870
871
872
873
874
875
876
877
878
879
880
881
882
883
884
885
886
887
888
889
890
891
892
893
894
895
896
897
898
899
900
901
902
903
904
905
906
907
908
909
910
911
912
913
914
915
916
917
918
919
920
921
922
923
924
925
926
927
928
929
930
931
932
933
934
935
936
937
938
939
940
941
942
943
944
945
946
947
948
949
950
951
952
953
954
955
956
957
958
959
960
961
962
963
964
965
966
967
968
969
970
971
972
973
974
975
976
977
978
979
980
981
982
983
984
985
986
987
988
989
990
991
992
993
994
995
996
997
998
999
1000
{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
"name": "C2W2.ipynb",
"version": "0.3.2",
"provenance": [],
"collapsed_sections": []
},
"kernelspec": {
"name": "python3",
"display_name": "Python 3"
},
"accelerator": "GPU"
},
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "x_0YAjGUiLoU",
"colab_type": "text"
},
"source": [
"## Линейная регрессия: переобучение и регуляризация \n",
"**Постановка задачи**: построить линейную модель для прогнозирования количества прокатов велосипедов в зависимости от календарных характеристик дня и погодных условий. Нужно так подобрать веса признаков, чтобы уловить все линейные зависимости в данных и в то же время не учесть лишние признаки, тогда модель не переобучится и будет делать достаточно точные предсказания на новых данных. Найденные линейные зависимости нужно будет интерпретировать, то есть понять, соответствует ли обнаруженная закономерность здравому смыслу. Основная цель задания --- на примере показать и объяснить, из-за чего возникает переобучение и как с ним можно бороться."
]
},
{
"cell_type": "code",
"metadata": {
"id": "ImiT21xph8Wd",
"colab_type": "code",
"colab": {}
},
"source": [
"import pandas as pd\n",
"import numpy as np\n",
"from matplotlib import pyplot as plt\n",
"%matplotlib inline"
],
"execution_count": 0,
"outputs": []
},
{
"cell_type": "markdown",
"metadata": {
"id": "ZMN-4gZtingR",
"colab_type": "text"
},
"source": [
"## Знакомство с данными"
]
},
{
"cell_type": "code",
"metadata": {
"id": "BZ767x9xiqaF",
"colab_type": "code",
"outputId": "392d8b6a-f5b6-4295-dd07-4f2cbf281dad",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 204
}
},
"source": [
"df = pd.read_csv(r'https://d3c33hcgiwev3.cloudfront.net/_1fbbe0f3404552777e1932b2a209e803_bikes_rent.csv?Expires=1564531200&Signature=hJpasl5k-hbQwS67n-RTvgUUxafF~fCbDAwrlWPRfmKbILu-Z32H88IthkWRzzuY~YwFPTuv7xi5x2Kn0QEKkAhyIbUr0kE-TK5yZtx~AzyCchWqYcZSFAKe2154-hwMxdt~yAuRftw06w7Z51QGIwcc76cn~0QB5HlGN9nIa-0_&Key-Pair-Id=APKAJLTNE6QMUY6HBC5A')\n",
"df.head()"
],
"execution_count": 80,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>season</th>\n",
" <th>yr</th>\n",
" <th>mnth</th>\n",
" <th>holiday</th>\n",
" <th>weekday</th>\n",
" <th>workingday</th>\n",
" <th>weathersit</th>\n",
" <th>temp</th>\n",
" <th>atemp</th>\n",
" <th>hum</th>\n",
" <th>windspeed(mph)</th>\n",
" <th>windspeed(ms)</th>\n",
" <th>cnt</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>6</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>14.110847</td>\n",
" <td>18.18125</td>\n",
" <td>80.5833</td>\n",
" <td>10.749882</td>\n",
" <td>4.805490</td>\n",
" <td>985</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>14.902598</td>\n",
" <td>17.68695</td>\n",
" <td>69.6087</td>\n",
" <td>16.652113</td>\n",
" <td>7.443949</td>\n",
" <td>801</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>8.050924</td>\n",
" <td>9.47025</td>\n",
" <td>43.7273</td>\n",
" <td>16.636703</td>\n",
" <td>7.437060</td>\n",
" <td>1349</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>8.200000</td>\n",
" <td>10.60610</td>\n",
" <td>59.0435</td>\n",
" <td>10.739832</td>\n",
" <td>4.800998</td>\n",
" <td>1562</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>9.305237</td>\n",
" <td>11.46350</td>\n",
" <td>43.6957</td>\n",
" <td>12.522300</td>\n",
" <td>5.597810</td>\n",
" <td>1600</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" season yr mnth holiday ... hum windspeed(mph) windspeed(ms) cnt\n",
"0 1 0 1 0 ... 80.5833 10.749882 4.805490 985\n",
"1 1 0 1 0 ... 69.6087 16.652113 7.443949 801\n",
"2 1 0 1 0 ... 43.7273 16.636703 7.437060 1349\n",
"3 1 0 1 0 ... 59.0435 10.739832 4.800998 1562\n",
"4 1 0 1 0 ... 43.6957 12.522300 5.597810 1600\n",
"\n",
"[5 rows x 13 columns]"
]
},
"metadata": {
"tags": []
},
"execution_count": 80
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "8pWpEA9Ci8Oe",
"colab_type": "text"
},
"source": [
"Для каждого дня проката известны следующие признаки (как они были указаны в источнике данных):\n",
"\n",
"* season: 1 - весна, 2 - лето, 3 - осень, 4 - зима\n",
"* yr: 0 - 2011, 1 - 2012\n",
"* mnth: от 1 до 12\n",
"* holiday: 0 - нет праздника, 1 - есть праздник\n",
"* weekday: от 0 до 6\n",
"* workingday: 0 - нерабочий день, 1 - рабочий день\n",
"* weathersit: оценка благоприятности погоды от 1 (чистый, ясный день) до 4 (ливень, туман)\n",
"* temp: температура в Цельсиях\n",
"* atemp: температура по ощущениям в Цельсиях\n",
"* hum: влажность\n",
"* windspeed(mph): скорость ветра в милях в час\n",
"* windspeed(ms): скорость ветра в метрах в секунду\n",
"* cnt: количество арендованных велосипедов (это целевой признак, его мы будем предсказывать) \n",
"\n",
"Итак, у нас есть вещественные, бинарные и номинальные (порядковые) признаки, и со всеми из них можно работать как с вещественными. С номинальныеми признаками тоже можно работать как с вещественными, потому что на них задан порядок. Давайте посмотрим на графиках, как целевой признак зависит от остальных"
]
},
{
"cell_type": "code",
"metadata": {
"id": "LAc7XL9AjS3J",
"colab_type": "code",
"outputId": "eaa306ea-0f5f-4fbf-8163-459319bf4885",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 609
}
},
"source": [
"fig, axes = plt.subplots(nrows=3, ncols=4, figsize=(15, 10))\n",
"for idx, feature in enumerate(df.columns[:-1]):\n",
" df.plot(feature, \"cnt\", subplots=True, kind=\"scatter\", ax=axes[int(idx/4), idx%4])"
],
"execution_count": 81,
"outputs": [
{
"output_type": "display_data",
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAA4UAAAJQCAYAAAA5VMGIAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nwPx/DQgWqTmBPHwAAAAASUVORK5CYII=\n",
"text/plain": [
"<Figure size 1080x720 with 12 Axes>"
]
},
"metadata": {
"tags": []
}
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "hjKZLGWNLjKF",
"colab_type": "text"
},
"source": [
"Доп вопросы:\n",
"\n",
"**Блок 1**. Ответьте на вопросы (каждый 0.5 балла):\n",
"\n",
"*Каков характер зависимости числа прокатов от месяца?*\n",
"\n",
"Кваддратический, ось симетрии параболы приходится примерно на шестой-седьмой меяц. На графике можно увидеть рост продаж, который начинается весной, достигает пиков в летний период и идет на спад в начале осени\n",
"\n",
"*Укажите один или два признака, от которых число прокатов скорее всего зависит линейно*\n",
"\n",
"Явно видна линейная зависимость целевой переменной от обоих температурных признаков признаков (temp и atemp), тем не менее наличие обоих в датафрейме избыточно и с точки зрения полезности их можно воспринимать как один"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "cYUxMGxfKSN9",
"colab_type": "text"
},
"source": [
"Более строго оценим уровень линейной зависимости между признаками и целевой переменной. Хорошей мерой линейной зависимости между двумя векторами является корреляция Пирсона."
]
},
{
"cell_type": "code",
"metadata": {
"id": "2JA7Qz83KUV1",
"colab_type": "code",
"outputId": "ac50ab22-e11b-4463-d67f-002de9b24a1a",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 221
}
},
"source": [
"for col in df.columns[:-1]:\n",
" print(\n",
" 'Корреляция между целевой переменной и признаком {} составляет: {}'\n",
" .format(col, df['cnt'].corr(df[col])))"
],
"execution_count": 82,
"outputs": [
{
"output_type": "stream",
"text": [
"Корреляция между целевой переменной и признаком season составляет: 0.4061003707986365\n",
"Корреляция между целевой переменной и признаком yr составляет: 0.5667097078680865\n",
"Корреляция между целевой переменной и признаком mnth составляет: 0.27997711221927124\n",
"Корреляция между целевой переменной и признаком holiday составляет: -0.06834771589248406\n",
"Корреляция между целевой переменной и признаком weekday составляет: 0.06744341241063045\n",
"Корреляция между целевой переменной и признаком workingday составляет: 0.061156063060520655\n",
"Корреляция между целевой переменной и признаком weathersit составляет: -0.2973912388346636\n",
"Корреляция между целевой переменной и признаком temp составляет: 0.6274940090334922\n",
"Корреляция между целевой переменной и признаком atemp составляет: 0.6310656998491815\n",
"Корреляция между целевой переменной и признаком hum составляет: -0.1006585621371552\n",
"Корреляция между целевой переменной и признаком windspeed(mph) составляет: -0.2345449974216702\n",
"Корреляция между целевой переменной и признаком windspeed(ms) составляет: -0.23454499742168924\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "l0XzJy2OOEIw",
"colab_type": "text"
},
"source": [
"В выборке есть признаки, коррелирующие с целевым, а значит, задачу можно решать линейными методами."
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "LPjlhBzfOQfE",
"colab_type": "text"
},
"source": [
"По графикам видно, что некоторые признаки похожи друг на друга. Поэтому давайте также посчитаем корреляции между вещественными признаками."
]
},
{
"cell_type": "code",
"metadata": {
"id": "d-UUgVK3OyWk",
"colab_type": "code",
"outputId": "ae551b20-724b-4b97-f738-8008badcf226",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 235
}
},
"source": [
"attrs = [col for col in df.columns if df[col].dtype == np.float]\n",
"df[attrs + ['cnt']].corr()"
],
"execution_count": 83,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>temp</th>\n",
" <th>atemp</th>\n",
" <th>hum</th>\n",
" <th>windspeed(mph)</th>\n",
" <th>windspeed(ms)</th>\n",
" <th>cnt</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>temp</th>\n",
" <td>1.000000</td>\n",
" <td>0.991702</td>\n",
" <td>0.126963</td>\n",
" <td>-0.157944</td>\n",
" <td>-0.157944</td>\n",
" <td>0.627494</td>\n",
" </tr>\n",
" <tr>\n",
" <th>atemp</th>\n",
" <td>0.991702</td>\n",
" <td>1.000000</td>\n",
" <td>0.139988</td>\n",
" <td>-0.183643</td>\n",
" <td>-0.183643</td>\n",
" <td>0.631066</td>\n",
" </tr>\n",
" <tr>\n",
" <th>hum</th>\n",
" <td>0.126963</td>\n",
" <td>0.139988</td>\n",
" <td>1.000000</td>\n",
" <td>-0.248489</td>\n",
" <td>-0.248489</td>\n",
" <td>-0.100659</td>\n",
" </tr>\n",
" <tr>\n",
" <th>windspeed(mph)</th>\n",
" <td>-0.157944</td>\n",
" <td>-0.183643</td>\n",
" <td>-0.248489</td>\n",
" <td>1.000000</td>\n",
" <td>1.000000</td>\n",
" <td>-0.234545</td>\n",
" </tr>\n",
" <tr>\n",
" <th>windspeed(ms)</th>\n",
" <td>-0.157944</td>\n",
" <td>-0.183643</td>\n",
" <td>-0.248489</td>\n",
" <td>1.000000</td>\n",
" <td>1.000000</td>\n",
" <td>-0.234545</td>\n",
" </tr>\n",
" <tr>\n",
" <th>cnt</th>\n",
" <td>0.627494</td>\n",
" <td>0.631066</td>\n",
" <td>-0.100659</td>\n",
" <td>-0.234545</td>\n",
" <td>-0.234545</td>\n",
" <td>1.000000</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" temp atemp ... windspeed(ms) cnt\n",
"temp 1.000000 0.991702 ... -0.157944 0.627494\n",
"atemp 0.991702 1.000000 ... -0.183643 0.631066\n",
"hum 0.126963 0.139988 ... -0.248489 -0.100659\n",
"windspeed(mph) -0.157944 -0.183643 ... 1.000000 -0.234545\n",
"windspeed(ms) -0.157944 -0.183643 ... 1.000000 -0.234545\n",
"cnt 0.627494 0.631066 ... -0.234545 1.000000\n",
"\n",
"[6 rows x 6 columns]"
]
},
"metadata": {
"tags": []
},
"execution_count": 83
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "owwZmKfoP_HV",
"colab_type": "text"
},
"source": [
"На диагоналях, как и полагается, стоят единицы. Однако в матрице имеются еще две пары сильно коррелирующих столбцов: temp и atemp (коррелируют по своей природе) и два windspeed (потому что это просто перевод одних единиц в другие). Далее мы увидим, что этот факт негативно сказывается на обучении линейной модели.\n",
"\n",
"Напоследок посмотрим средние признаков (метод mean), чтобы оценить масштаб признаков и доли 1 у бинарных признаков."
]
},
{
"cell_type": "code",
"metadata": {
"id": "vb3G51JGQH3U",
"colab_type": "code",
"outputId": "f0040378-ecfb-4e6b-f01d-fc4d2ccc47e3",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 85
}
},
"source": [
"bin_attrib = [col for col in df.columns if len(df[col].value_counts()) == 2]\n",
"df[bin_attrib].describe().loc['mean']"
],
"execution_count": 84,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"yr 0.500684\n",
"holiday 0.028728\n",
"workingday 0.683995\n",
"Name: mean, dtype: float64"
]
},
"metadata": {
"tags": []
},
"execution_count": 84
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "80NPJFCDQK8j",
"colab_type": "text"
},
"source": [
"Признаки имеют разный масштаб, значит для дальнейшей работы нам лучше нормировать матрицу объекты-признаки."
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "GffOcOHQRjoz",
"colab_type": "text"
},
"source": [
"## Проблема первая: коллинеарные признаки\n",
"\n",
"Итак, в наших данных один признак дублирует другой, и есть еще два очень похожих. Конечно, мы могли бы сразу удалить дубликаты, но давайте посмотрим, как бы происходило обучение модели, если бы мы не заметили эту проблему.\n",
"\n",
"Для начала проведем масштабирование, или стандартизацию признаков: из каждого признака вычтем его среднее и поделим на стандартное отклонение. \n",
"\n",
"Кроме того, нужно перемешать выборку, это потребуется для кросс-валидации."
]
},
{
"cell_type": "code",
"metadata": {
"id": "NfRySo54Rqrj",
"colab_type": "code",
"colab": {}
},
"source": [
"from sklearn.preprocessing import scale\n",
"from sklearn.utils import shuffle\n",
"\n",
"df_shuffled = shuffle(df, random_state=123)\n",
"X = scale(df_shuffled[df_shuffled.columns[:-1]])\n",
"y = df_shuffled[\"cnt\"]"
],
"execution_count": 0,
"outputs": []
},
{
"cell_type": "markdown",
"metadata": {
"id": "xuiaKqS4R3ub",
"colab_type": "text"
},
"source": [
"Обучим линейную регрессию на наших данных и посмотрим на веса признаков."
]
},
{
"cell_type": "code",
"metadata": {
"id": "Dbi-0KJMR5gM",
"colab_type": "code",
"colab": {}
},
"source": [
"from sklearn.linear_model import LinearRegression"
],
"execution_count": 0,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "Z0HXh_WLR7Vr",
"colab_type": "code",
"colab": {}
},
"source": [
"lin_model = LinearRegression()\n",
"lin_model.fit(X, y)\n",
"weights = zip(lin_model.coef_, df.columns)"
],
"execution_count": 0,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "6Kz9xD4RSu-7",
"colab_type": "code",
"outputId": "bcd17e4a-77db-406f-d3b7-b8eaf85249ff",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 221
}
},
"source": [
"list(weights)"
],
"execution_count": 88,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"[(570.8675887934525, 'season'),\n",
" (1021.9652921309369, 'yr'),\n",
" (-141.30438378580345, 'mnth'),\n",
" (-86.75613647415624, 'holiday'),\n",
" (137.22482362623418, 'weekday'),\n",
" (56.39056950314733, 'workingday'),\n",
" (-330.2332887484121, 'weathersit'),\n",
" (367.47338726750786, 'temp'),\n",
" (585.5559979631937, 'atemp'),\n",
" (-145.6063153911189, 'hum'),\n",
" (12458200269331.953, 'windspeed(mph)'),\n",
" (-12458200269530.414, 'windspeed(ms)')]"
]
},
"metadata": {
"tags": []
},
"execution_count": 88
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "qI0VPQ_u54tg",
"colab_type": "text"
},
"source": [
"Чтобы понять, почему так произошло, вспомним аналитическую формулу, по которой вычисляются веса линейной модели в методе наименьших квадратов:\n",
"\n",
"$w = (X^TX)^{-1} X^T y$.\n",
"\n",
"Если в X есть коллинеарные (линейно-зависимые) столбцы, матрица $X^TX$ становится вырожденной, и формула перестает быть корректной. Чем более зависимы признаки, тем меньше определитель этой матрицы и тем хуже аппроксимация $Xw \\approx y$. Такая ситуацию называют проблемой мультиколлинеарности, вы обсуждали ее на лекции.\n",
"\n",
"С парой temp-atemp чуть менее коррелирующих переменных такого не произошло, однако на практике всегда стоит внимательно следить за коэффициентами при похожих признаках. \n",
"\n",
"Решение проблемы мультиколлинеарности состоит в регуляризации линейной модели. К оптимизируемому функционалу прибавляют L1 или L2 норму весов, умноженную на коэффициент регуляризации α . В первом случае метод называется Lasso, а во втором --- Ridge. Подробнее об этом также рассказано в лекции.\n",
"\n",
"Обучим регрессоры Ridge и Lasso с параметрами по умолчанию и убедитесь, что проблема с весами решилась."
]
},
{
"cell_type": "code",
"metadata": {
"id": "MDZQEr8V6a8e",
"colab_type": "code",
"colab": {}
},
"source": [
"from sklearn.linear_model import Lasso, Ridge"
],
"execution_count": 0,
"outputs": []
},
{
"cell_type": "markdown",
"metadata": {
"id": "xEyg750n6ktY",
"colab_type": "text"
},
"source": [
"### L1 - регуляризация"
]
},
{
"cell_type": "code",
"metadata": {
"id": "8_ye7JqL6pX6",
"colab_type": "code",
"outputId": "76322057-6d44-4462-8044-adeac806c96c",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 221
}
},
"source": [
"lasso_regressor = Lasso()\n",
"lasso_regressor.fit(X, y)\n",
"list(zip(df.columns[:-1], lasso_regressor.coef_))"
],
"execution_count": 90,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"[('season', 560.2416160308869),\n",
" ('yr', 1019.4634940657196),\n",
" ('mnth', -128.73062703678752),\n",
" ('holiday', -86.15278133371116),\n",
" ('weekday', 137.34789390496314),\n",
" ('workingday', 55.212370641356685),\n",
" ('weathersit', -332.3698569623484),\n",
" ('temp', 376.3632362096995),\n",
" ('atemp', 576.5307935045503),\n",
" ('hum', -144.1291550034858),\n",
" ('windspeed(mph)', -197.13968940248557),\n",
" ('windspeed(ms)', -2.8050167469807684e-08)]"
]
},
"metadata": {
"tags": []
},
"execution_count": 90
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "qJlipb5E6kmZ",
"colab_type": "text"
},
"source": [
"### L2 - регуляризация"
]
},
{
"cell_type": "code",
"metadata": {
"id": "sdZeFMn263b7",
"colab_type": "code",
"outputId": "3290e770-df72-4241-9e37-912e0d574671",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 221
}
},
"source": [
"ridge_regressor = Ridge()\n",
"ridge_regressor.fit(X, y)\n",
"list(zip(df.columns[:-1], ridge_regressor.coef_))"
],
"execution_count": 91,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"[('season', 563.0645722520175),\n",
" ('yr', 1018.9483787875301),\n",
" ('mnth', -131.873320282477),\n",
" ('holiday', -86.74609799709219),\n",
" ('weekday', 138.0051111787191),\n",
" ('workingday', 55.90311037506478),\n",
" ('weathersit', -332.34978849907395),\n",
" ('temp', 386.4578891919065),\n",
" ('atemp', 566.3470470600686),\n",
" ('hum', -145.07132729867178),\n",
" ('windspeed(mph)', -99.25944108179063),\n",
" ('windspeed(ms)', -99.25944115434177)]"
]
},
"metadata": {
"tags": []
},
"execution_count": 91
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "zg5XFtUB7VDJ",
"colab_type": "text"
},
"source": [
"Не сказал бы конечно что проблема решена\n",
"\n",
"**Блок 2**. Поясните, каким образом введение регуляризации решает проблему с весами и мультиколлинеарностью.\n",
"\n",
"Но в теории - в процессе регуляризации происходит штрафование за абсолютное значение суммы весов, что приводит к одновременной минимизации как ошибки, так и этого значения, в поисках оптимума должны быть отброшены слишком большие веса при условно равном качестве, решая таким образом проблему мультиколлинеарности\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "V-pdWuBY8Jak",
"colab_type": "text"
},
"source": [
"## Проблема вторая: неинформативные признаки\n",
"\n",
"\n",
"В отличие от L2-регуляризации, L1 обнуляет веса при некоторых признаках, пронаблюдаем, как меняются веса при увеличении коэффициента регуляризации α (в лекции коэффициент при регуляризаторе мог быть обозначен другой буквой)."
]
},
{
"cell_type": "code",
"metadata": {
"id": "BNGa_OR-8cE-",
"colab_type": "code",
"colab": {}
},
"source": [
"alphas = np.arange(1, 500, 50)\n",
"coefs_lasso = np.zeros((alphas.shape[0], X.shape[1])) \n",
"coefs_ridge = np.zeros((alphas.shape[0], X.shape[1]))\n",
"\n",
"\n",
"def train(regressor_creator, result_matrix):\n",
" for row_index, row in enumerate(result_matrix):\n",
" regressor = regressor_creator(alphas[row_index])\n",
" regressor.fit(X, y)\n",
" for i, _ in enumerate(row):\n",
" row[i] = regressor.coef_[i]\n",
"\n",
" \n",
" \n",
"train(lambda alpha: Lasso(alpha=alpha), coefs_lasso)\n",
"train(lambda alpha: Ridge(alpha=alpha), coefs_ridge)"
],
"execution_count": 0,
"outputs": []
},
{
"cell_type": "markdown",
"metadata": {
"id": "5aQYe_amBspB",
"colab_type": "text"
},
"source": [
"Визуализируем динамику весов при увеличении параметра регуляризации:"
]
},
{
"cell_type": "code",
"metadata": {
"id": "PBW7B01-BqEt",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 700
},
"outputId": "595ac07a-789d-4477-b108-dc298ff0f4b7"
},
"source": [
"plt.figure(figsize=(8, 5))\n",
"for coef, feature in zip(coefs_lasso.T, df.columns):\n",
" plt.plot(alphas, coef, label=feature, color=np.random.rand(3))\n",
"plt.legend(loc=\"upper right\", bbox_to_anchor=(1.4, 0.95))\n",
"plt.xlabel(\"alpha\")\n",
"plt.ylabel(\"feature weight\")\n",
"plt.title(\"Lasso\")\n",
"\n",
"plt.figure(figsize=(8, 5))\n",
"for coef, feature in zip(coefs_ridge.T, df.columns):\n",
" plt.plot(alphas, coef, label=feature, color=np.random.rand(3))\n",
"plt.legend(loc=\"upper right\", bbox_to_anchor=(1.4, 0.95))\n",
"plt.xlabel(\"alpha\")\n",
"plt.ylabel(\"feature weight\")\n",
"plt.title(\"Ridge\")"
],
"execution_count": 94,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"Text(0.5, 1.0, 'Ridge')"
]
},
"metadata": {
"tags": []
},
"execution_count": 94
},
{
"output_type": "display_data",
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAqoAAAFNCAYAAADILE3NAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nRK5CYII=\n",
"text/plain": [
"<Figure size 576x360 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "display_data",
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAqoAAAFNCAYAAADILE3NAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nJSIiIqJO6f8DdtIGbP4fmJMAAAAASUVORK5CYII=\n",
"text/plain": [
"<Figure size 576x360 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "csWFwTO1BzBA",
"colab_type": "text"
},
"source": [
"Ответы на следующие вопросы можно давать, глядя на графики или выводя коэффициенты на печать.\n",
"\n",
"**Блок 3**. Ответьте на вопросы (каждый 0.25 балла):\n",
"\n",
"*Какой регуляризатор (Ridge или Lasso) агрессивнее уменьшает веса при одном и том же alpha?* \n",
"Lasso \n",
"\n",
"*Что произойдет с весами Lasso, если alpha сделать очень большим? Поясните, почему так происходит.*\n",
" \n",
"Увеличение альфа приводит к более сильному штрафованию значения весов, что в свою очередь не позволит достичь оптимального качества по причине того что слагамое, отвечающее за регуляризацию, будет сильно больше среднеквадратичной ошибки, а оптимальное значение этого слагаемого достигается при нулевых весах.\n",
"\n",
"*Можно ли утверждать, что Lasso исключает один из признаков windspeed при любом значении alpha > 0? А Ridge? Ситается, что регуляризатор исключает признак, если коэффициент при нем < 1e-3.*\n",
"\n",
"Верно, вне зависимости от значения alpha вес признака windspeed(ms) близок к нулю что практически тождествленно игнорированию, в случае же с Ridge-регуляризацией оба признака windspeed имеют значения отличные от нуля\n",
"\n",
"*Какой из регуляризаторов подойдет для отбора неинформативных признаков?*\n",
"Lasso, даже на предыдущем примере видна агрессивная политика, сводящаяся к исключению подобных признаков путем уменьшения их весов до нуля"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "1CPEtyeYEIZw",
"colab_type": "text"
},
"source": [
"Далее будем работать с Lasso.\n",
"\n",
"Итак, мы видим, что при изменении alpha модель по-разному подбирает коэффициенты признаков. Нам нужно выбрать наилучшее alpha.\n",
"\n",
"Для этого, во-первых, нам нужна метрика качества. Будем использовать в качестве метрики сам оптимизируемый функционал метода наименьших квадратов, то есть Mean Square Error.\n",
"\n",
"Во-вторых, нужно понять, на каких данных эту метрику считать. Нельзя выбирать alpha по значению MSE на обучающей выборке, потому что тогда мы не сможем оценить, как модель будет делать предсказания на новых для нее данных. Если мы выберем одно разбиение выборки на обучающую и тестовую (это называется holdout), то настроимся на конкретные \"новые\" данные, и вновь можем переобучиться. Поэтому будем делать несколько разбиений выборки, на каждом пробовать разные значения alpha, а затем усреднять MSE. Удобнее всего делать такие разбиения кросс-валидацией, то есть разделить выборку на K частей, или блоков, и каждый раз брать одну из них как тестовую, а из оставшихся блоков составлять обучающую выборку.\n",
"\n",
"Делать кросс-валидацию для регрессии в sklearn совсем просто: для этого есть специальный регрессор, LassoCV, который берет на вход список из alpha и для каждого из них вычисляет MSE на кросс-валидации. После обучения (если оставить параметр cv=3 по умолчанию) регрессор будет содержать переменную mse_path_, матрицу размера len(alpha) x k, k = 3 (число блоков в кросс-валидации), содержащую значения MSE на тесте для соответствующих запусков. Кроме того, в переменной alpha_ будет храниться выбранное значение параметра регуляризации, а в coef_, традиционно, обученные веса, соответствующие этому alpha_.\n",
"\n",
"Обратите внимание, что регрессор может менять порядок, в котором он проходит по alphas; для сопоставления с матрицей MSE лучше использовать переменную регрессора alphas_."
]
},
{
"cell_type": "code",
"metadata": {
"id": "I2n6XwQbEP3g",
"colab_type": "code",
"colab": {}
},
"source": [
"from sklearn.linear_model import LassoCV"
],
"execution_count": 0,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "mXNBtKuiEVWJ",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 605
},
"outputId": "12561751-b583-4934-da62-c81a00df9bb4"
},
"source": [
"alphas = np.arange(1, 100, 5)\n",
"lassocv_regressor = LassoCV(alphas=alphas)\n",
"lassocv_regressor.fit(X, y)\n",
"mse_path = lassocv_regressor.mse_path_\n",
"regressor_alphas = lassocv_regressor.alphas_\n",