For the HMEQ dataset, you are given a target variable BAD Your task is to apply any binary classification algorithm to the dataset, employing a suitable training and test split Use a linear regression model to model the LGD based on the independent variables provided in the dataset BAD LOAN MORTDUE VALUE REASON JOB YOJ DEROG DELINQ CLAGE NINQ CLNO DEBTINC 1 1100 25860 39025 HomeImp Other 10 05 2023 0 0 94 366 666 667 1 9 1 1300 70053 68400 HomeImp Other 07 01 1900 0 2 12 183 333 333 0 14 1 1500 13500 16700 HomeImp Other 04 01 1900 0 0 14 946 666 667 1 10 1 1500 0 1700 97800 112000 HomeImp Office 03 01 1900 0 0 93 333 333 333 0 14 1 1700 30548 40320 HomeImp Other 09 01 1900 0 0 10 146 600 191 1 8 37 113 613 558 1 1800 48649 57037 HomeImp Other 05 01 1900 3 2 77 1 1 17 1 1800 28502 43034 HomeImp Other 11 01 1900 0 0 88 766 029 879 0 8 36 884 894 093 1 2000 32700 46740 HomeImp Other 03 01 1900 0 2 21 693 333 333 1 12 1 2000 62250 HomeImp Sales 16 01 1900 0 0 115 8 0 13 1 2000 22608 18 01 1900 1 2000 20627 29800 HomeImp Office 11 01 1900 0 1 12 253 333 333 1 9 1 2000 45000 55000 HomeImp Other 03 01 1900 0 0 86 066 666 667 2 25 0 2000 64536 87400 Mgr 02 05 2023 0 0 14 713 333 333 0 24 1 2100 71000 83850 HomeImp Other 08 01 1900 0 1 123 0 16 1 2200 24280 34687 HomeImp Other 0 1 30 086 666 667 0 8 1 2200 90957 102600 HomeImp Mgr 07 01 1900 2 6 122 9 1 22 1 2200 23030 19 01 1900 37 113 122 995 1 2300 28192 40150 HomeImp Other 04 05 2023 0 0 54 6 1 16 0 2300 102370 120953 HomeImp Office 02 01 1900 0 0 90 992 533 467 0 13 31 588 503 178 1 2300 37626 46200 HomeImp Other 03 01 1900 0 1 12 226 666 667 1 14 1 2400 50000 73395 HomeImp ProfExe 05 01 1900 1 0 1 0 1 2400 28000 40800 HomeImp Mgr 12 01 1900 0 0 67 2 2 22 1 2400 18000 HomeImp Mgr 22 01 1900 2 12 173 333 333 0 10 1 2400 17180 HomeImp Other 0 0 14 566 666 667 3 4 1 2400 34863 47471 HomeImp Mgr 12 01 1900 0 0 70 491 080 032 1 21 38 263 600 731 0 2400 98449 117195 HomeImp Office 04 01 1900 0 0 93 811 774 855 0 13 29 681 827 045 1 2500 15000 20200 HomeImp 18 01 1900 0 0 13 606 666 667 1 19 1 2500 25116 36350 HomeImp Other 10 01 1900 1 2 27 696 666 667 0 9 0 2500 7229 44516 HomeImp Self 0 0 208 0 12 0 2500 71408 78600 HomeImp ProfExe 08 01 1900 0 0 25 573 333 333 0 12 1 2800 50795 63100 HomeImp Self 26 01 1900 2 15 14 563 333 333 3 45 1 2800 4000 60850 HomeImp Other 16 01 1900 4 0 11 263 333 333 2 9 1 2900 78600 113000 DebtCon ProfExe 06 01 1900 1 0 16 533 333 333 2 26 0 2900 103949 112505 HomeImp Office 01 01 1900 0 0 9 610 232 967 0 13 30 051 136 286 0 2900 104373 120702 HomeImp Office 02 01 1900 0 0 10 154 029 753 0 13 29 915 859 028 1 2900 7750 67996 HomeImp Other 16 01 1900 3 0 12 220 466 276 2 8 36 211 347 998 1 2900 61962 70915 DebtCon Mgr 02 01 1900 0 0 28 280 165 924 3 37 4 920 639 579 0 3000 104570 121729 HomeImp Office 02 01 1900 0 0 85 884 371 895 0 14 32 059 783 267 1 3000 7000 20300 HomeImp Other 03 01 1900 0 0 50 8 5 9 1 3000 8800 HomeImp Other 02 01 1900 0 1 77 766 666 667 0 3 1 3000 33000 HomeImp Other 01 01 1900 0 1 23 Mrz 1 2 1 3000 119826 193500 HomeImp Other 08 01 1900 0 0 13 003 335 846 0 27 1 3000 20000 29750 DebtCon Other 02 01 1900 0 0 18 706 666 667 0 12 1 3000 14500 HomeImp Other 03 01 1900 0 0 09 Mrz 14 2

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For the HMEQ dataset, you are given a target variable BAD. Your task is to apply any binary classification algorithm to the dataset, employing a

For the HMEQ dataset, you are given a target variable BAD. Your task is to apply any binary classification algorithm to the dataset, employing a suitable training and test split.

Use a linear regression model to model the LGD based on the independent variables provided in the dataset.

BAD	LOAN	MORTDUE	VALUE	REASON	JOB	YOJ	DEROG	DELINQ	CLAGE	NINQ	CLNO	DEBTINC
1	1100	25860	39025	HomeImp	Other	10.05.2023	0	0	94.366.666.667	1	9
1	1300	70053	68400	HomeImp	Other	07.01.1900	0	2	12.183.333.333	0	14
1	1500	13500	16700	HomeImp	Other	04.01.1900	0	0	14.946.666.667	1	10
1	1500
0	1700	97800	112000	HomeImp	Office	03.01.1900	0	0	93.333.333.333	0	14
1	1700	30548	40320	HomeImp	Other	09.01.1900	0	0	10.146.600.191	1	8	37.113.613.558
1	1800	48649	57037	HomeImp	Other	05.01.1900	3	2	77.1	1	17
1	1800	28502	43034	HomeImp	Other	11.01.1900	0	0	88.766.029.879	0	8	36.884.894.093
1	2000	32700	46740	HomeImp	Other	03.01.1900	0	2	21.693.333.333	1	12
1	2000		62250	HomeImp	Sales	16.01.1900	0	0	115.8	0	13
1	2000	22608				18.01.1900
1	2000	20627	29800	HomeImp	Office	11.01.1900	0	1	12.253.333.333	1	9
1	2000	45000	55000	HomeImp	Other	03.01.1900	0	0	86.066.666.667	2	25
0	2000	64536	87400		Mgr	02.05.2023	0	0	14.713.333.333	0	24
1	2100	71000	83850	HomeImp	Other	08.01.1900	0	1	123	0	16
1	2200	24280	34687	HomeImp	Other		0	1	30.086.666.667	0	8
1	2200	90957	102600	HomeImp	Mgr	07.01.1900	2	6	122.9	1	22
1	2200	23030				19.01.1900						37.113.122.995
1	2300	28192	40150	HomeImp	Other	04.05.2023	0	0	54.6	1	16
0	2300	102370	120953	HomeImp	Office	02.01.1900	0	0	90.992.533.467	0	13	31.588.503.178
1	2300	37626	46200	HomeImp	Other	03.01.1900	0	1	12.226.666.667	1	14
1	2400	50000	73395	HomeImp	ProfExe	05.01.1900	1	0		1	0
1	2400	28000	40800	HomeImp	Mgr	12.01.1900	0	0	67.2	2	22
1	2400	18000		HomeImp	Mgr	22.01.1900		2	12.173.333.333	0	10
1	2400		17180	HomeImp	Other		0	0	14.566.666.667	3	4
1	2400	34863	47471	HomeImp	Mgr	12.01.1900	0	0	70.491.080.032	1	21	38.263.600.731
0	2400	98449	117195	HomeImp	Office	04.01.1900	0	0	93.811.774.855	0	13	29.681.827.045
1	2500	15000	20200	HomeImp		18.01.1900	0	0	13.606.666.667	1	19
1	2500	25116	36350	HomeImp	Other	10.01.1900	1	2	27.696.666.667	0	9
0	2500	7229	44516	HomeImp	Self		0	0	208	0	12
0	2500	71408	78600	HomeImp	ProfExe	08.01.1900	0	0	25.573.333.333	0	12
1	2800	50795	63100	HomeImp	Self	26.01.1900	2	15	14.563.333.333	3	45
1	2800	4000	60850	HomeImp	Other	16.01.1900	4	0	11.263.333.333	2	9
1	2900	78600	113000	DebtCon	ProfExe	06.01.1900	1	0	16.533.333.333	2	26
0	2900	103949	112505	HomeImp	Office	01.01.1900	0	0	9.610.232.967	0	13	30.051.136.286
0	2900	104373	120702	HomeImp	Office	02.01.1900	0	0	10.154.029.753	0	13	29.915.859.028
1	2900	7750	67996	HomeImp	Other	16.01.1900	3	0	12.220.466.276	2	8	36.211.347.998
1	2900	61962	70915	DebtCon	Mgr	02.01.1900	0	0	28.280.165.924	3	37	4.920.639.579
0	3000	104570	121729	HomeImp	Office	02.01.1900	0	0	85.884.371.895	0	14	32.059.783.267
1	3000	7000	20300	HomeImp	Other	03.01.1900	0	0	50.8	5	9
1	3000		8800	HomeImp	Other	02.01.1900	0	1	77.766.666.667	0	3
1	3000		33000	HomeImp	Other	01.01.1900	0	1	23. Mrz	1	2
1	3000	119826	193500	HomeImp	Other	08.01.1900	0	0	13.003.335.846	0	27
1	3000	20000	29750	DebtCon	Other	02.01.1900	0	0	18.706.666.667	0	12
1	3000		14500	HomeImp	Other	03.01.1900	0	0	09. Mrz	14	2

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It appears that you have provided a dataset with some missing values and you would like to apply binary classification and linear regression to the da... blur-text-image