Using the programming language R, I need this code written from the screenshots provided below.
# Install package needed for this chapter install.packages("neuralnet") library(neuralnet) # Read in the data, shrink the data set to 500 records for a brief example dat net. dat Sweights tai] (.1) 1.31 1.4) (1.) 20.26862723968 1.98409776095 -4.21501351020 -12.6625102757 2.38765287020 1.28655442285 0.07598583361 -11.7919510406 (3. -5.18555529806 2.11086215444 -1.3861 5119306 -12.8315789302 [4.) -2.86032075459 1.15479552678 -23.55720485569 -12.1569875918 is. 145.43394037545 1.31334455201 -216.15493978072 -9.7583566078 (6) 68.15219222490 0.51288518377 -88.49607577815-779.8609668030 17. j 18. 30925574426 -1.40459327477 -354.6413787 3417 -278.3134848211 18. i 20.89341534372 3.43861894093 -10.60824199593 -14.2296267695 to.) 0.64098186374 0.02226095477 -0.97210259317 0.2875842217 0.02247174954 0.06629281727 0.06140611074 -1.9144937039 -3.80888610724 0.12568711841 -27.09423285766 37.95499308980 -1.14953984533 -217.5088510080S -9.7275105196 (13.) 143.24439499695 -0.57586560469 -242.25185180908 -274. 5034263670 (14.j 101.20200302147 1.35360109677 -206.14641179684 -7.5798165443 (15.) -30.45187266047 1.15113413360 29.28072169454 280.9296112476 (16.) 15.37164835196 1.26358693220 15.05258143017 -147.5215948723 (17.1 68.33993182866 0.52276340064 58.01743974096 -180.0309206090 118.) 24.04194814351 -0.36301830646 -418. 08741080128 - 1163.90511693.87 1.71 1.81 1. 30255372410 -84.4634256723 1.2350412314 2.389993251084 1.79824209242 0.67795966242.0235641336 2.864195749932 0.73749225007 4.4980709029 -2.4195802111 3.369635177742 14.1 1.26433664565 9.07944057612.4771845190 3.104071868407 (5.) -0. 30428614127 -712. 3014162891 4.2249842034 1. 592874329153 (6.) 0.06838158334 15. 2124814279 2.0672397196 1.874275565433 [7.) -0.07064580572 -7.4879404397 3.8932703085 2.256141936933 18. i 0.46664940670 -1.5788330178 1.6126879878 2.370483043966 1o. -1.84620678525 -1.8700388385 0.912720092 -0.001013202215 (10.) 1. 37378519549 1.2233383212 -1.2300424184 -1.757894195465 0.46022152040 -0.7475249540 14.6520289711 1.845910952708 2. 50368930711 26.05631 59331 3.6337255768 -2.406745572030 0.85174247572 -708.87390651941.7866343716 -1.190241223912 0.28635046928 -709.5875839125 1.8894612749 -0.341263601485 1.10462814506 35.23330037742.3335174450 -0.406102118852 116.1 0.931671 50795 -2.32761 56420 5.4529357228 -0.396604103267 (17.) 0.29962956184 6.4378904917 -62.8899443828 1.193303844885 0.67729658018 18.60913799153.5815392142 -0.900293754216 (1.) [2.] (2.) # In the second matrix, #rows represent the 8 # hidden nodes and one #constant input, while the #column represents the #single output, income2. [[1]][[2]] [.1) (1.) 1.13981 565180 (2.) -16.25557629348 (3.) -1.03901 347047 53.00991185515 17.662 50969761 [6.] -3.27460636456 3.62327351390 0.04100428353 0.39716010807 NOUS
