Oct-03-2022, 05:29 AM
I am new to python and I do not no how to approach to this problem. please suggest me how to do it. Its really important for me
The consumption function captures one of the key relationships in economic. It expresses consumption as a function of disposal income, where disposal income is income after taxes. The attached file “Assignment 2 – Dataset ” shows data of average US annual consumption (in $) and disposable income (in $) for the years 2000 to 2016.
1. Develop a Neural Network (NN) prediction model for consumption.
Dataset is given below:
Date Consumption Income
Q1, 2000 28634 31192
Q2, 2000 28837 31438
Q3, 2000 29039 31719
Q4, 2000 29220 31742
Q1, 2001 29276 31940
Q2, 2001 29282 31836
Q3, 2001 29313 32504
Q4, 2001 29685 32020
Q1, 2002 29709 32728
Q2, 2002 29795 32821
Q3, 2002 29927 32696
Q4, 2002 30014 32773
Q1, 2003 30084 32796
Q2, 2003 30351 33197
Q3, 2003 30722 33657
Q4, 2003 30887 33713
Q1, 2004 31127 33893
Q2, 2004 31261 34152
Q3, 2004 31481 34247
Q4, 2004 31725 34589
Q1, 2005 31900 34183
Q2, 2005 32178 34380
Q3, 2005 32345 34469
Q4, 2005 32386 34666
Q1, 2006 32677 35380
Q2, 2006 32777 35354
Q3, 2006 32884 35363
Q4, 2006 33134 35734
Q1, 2007 33235 35889
Q2, 2007 33273 35878
Q3, 2007 33335 35880
Q4, 2007 33292 35819
Q1, 2008 33150 35998
Q2, 2008 33134 36677
Q3, 2008 32814 35747
Q4, 2008 32344 35892
Q1, 2009 32167 35752
Q2, 2009 31957 35932
Q3, 2009 32076 35456
Q4, 2009 31999 35328
Q1, 2010 32106 35293
Q2, 2010 32308 35686
Q3, 2010 32451 35791
Q4, 2010 32717 35967
Q1, 2011 32826 36346
Q2, 2011 32836 36228
Q3, 2011 32913 36347
Q4, 2011 32959 36299
Q1, 2012 33104 36832
Q2, 2012 33105 37054
Q3, 2012 33128 36963
Q4, 2012 33156 37860
Q1, 2013 33263 36226
Q2, 2013 33280 36380
Q3, 2013 33370 36522
Q4, 2013 33585 36528
Q1, 2014 33688 36872
Q2, 2014 33946 37289
Q3, 2014 34190 37587
Q4, 2014 34508 37907
Q1, 2015 34659 38033
Q2, 2015 34850 38336
Q3, 2015 35015 38571
Q4, 2015 35147 38785
Q1, 2016 35236 38927
Q2, 2016 35550 39148
Q3, 2016 35743 39354
Q4, 2016 35987 39254
The consumption function captures one of the key relationships in economic. It expresses consumption as a function of disposal income, where disposal income is income after taxes. The attached file “Assignment 2 – Dataset ” shows data of average US annual consumption (in $) and disposable income (in $) for the years 2000 to 2016.
1. Develop a Neural Network (NN) prediction model for consumption.
Dataset is given below:
Date Consumption Income
Q1, 2000 28634 31192
Q2, 2000 28837 31438
Q3, 2000 29039 31719
Q4, 2000 29220 31742
Q1, 2001 29276 31940
Q2, 2001 29282 31836
Q3, 2001 29313 32504
Q4, 2001 29685 32020
Q1, 2002 29709 32728
Q2, 2002 29795 32821
Q3, 2002 29927 32696
Q4, 2002 30014 32773
Q1, 2003 30084 32796
Q2, 2003 30351 33197
Q3, 2003 30722 33657
Q4, 2003 30887 33713
Q1, 2004 31127 33893
Q2, 2004 31261 34152
Q3, 2004 31481 34247
Q4, 2004 31725 34589
Q1, 2005 31900 34183
Q2, 2005 32178 34380
Q3, 2005 32345 34469
Q4, 2005 32386 34666
Q1, 2006 32677 35380
Q2, 2006 32777 35354
Q3, 2006 32884 35363
Q4, 2006 33134 35734
Q1, 2007 33235 35889
Q2, 2007 33273 35878
Q3, 2007 33335 35880
Q4, 2007 33292 35819
Q1, 2008 33150 35998
Q2, 2008 33134 36677
Q3, 2008 32814 35747
Q4, 2008 32344 35892
Q1, 2009 32167 35752
Q2, 2009 31957 35932
Q3, 2009 32076 35456
Q4, 2009 31999 35328
Q1, 2010 32106 35293
Q2, 2010 32308 35686
Q3, 2010 32451 35791
Q4, 2010 32717 35967
Q1, 2011 32826 36346
Q2, 2011 32836 36228
Q3, 2011 32913 36347
Q4, 2011 32959 36299
Q1, 2012 33104 36832
Q2, 2012 33105 37054
Q3, 2012 33128 36963
Q4, 2012 33156 37860
Q1, 2013 33263 36226
Q2, 2013 33280 36380
Q3, 2013 33370 36522
Q4, 2013 33585 36528
Q1, 2014 33688 36872
Q2, 2014 33946 37289
Q3, 2014 34190 37587
Q4, 2014 34508 37907
Q1, 2015 34659 38033
Q2, 2015 34850 38336
Q3, 2015 35015 38571
Q4, 2015 35147 38785
Q1, 2016 35236 38927
Q2, 2016 35550 39148
Q3, 2016 35743 39354
Q4, 2016 35987 39254