Exercícios Práticos
Enviar por Favor para o E-mail da Disciplina:
gestao.estat.cert@gmail.com
Coloque seu nome o número do exercício e se se trata de exercício pratico ou teórico no assunto do e-mail
O SAS (linguagem de computação, principal habilidade de mercado para os tomadores de decisão em empresas do Brasil, versão gratuita excelente) e o Weka (principal programa para ensino de IA do mundo).
Exercício 1 Pratico:
Invente um exemplo (se inventar, envie uma copia para gasarrie@usp,br) para aplicar ML Supervisionado para Classificação ou troque os sinais de interrogação pelos últimos dígitos do seu numero USP no arquivo do Dinheiro Falsificado, Dead Line: 3/3/2023 . Rode uma rede neural com 1-2-3 camadas de neurônios:
@RELATION banco
@ATTRIBUTE Length REAL
@ATTRIBUTE Left REAL
@ATTRIBUTE Right REAL
@ATTRIBUTE Bottom REAL
@ATTRIBUTE Top REAL
@ATTRIBUTE Diagonal REAL
@ATTRIBUTE Class {FALSE,TRUE}
@DATA
214.?,13?,13?.?,9,9.?,141,FALSE
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214.8,129.7,129.7,8.7,9.6,142.2,FALSE
214.8,129.7,129.6,7.5,10.4,142,FALSE
215,129.6,129.7,10.4,7.7,141.8,FALSE
215.7,130.8,130.5,9,10.1,141.4,FALSE
215.5,129.5,129.7,7.9,9.6,141.6,FALSE
214.5,129.6,129.2,7.2,10.7,141.7,FALSE
214.9,129.4,129.7,8.2,11,141.9,FALSE
215.2,130.4,130.3,9.2,10,140.7,FALSE
215.3,130.4,130.3,7.9,11.7,141.8,FALSE
215.1,129.5,129.6,7.7,10.5,142.2,FALSE
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215,129.9,129.3,8.4,10,141.4,FALSE
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215.7,130.2,130,8.7,10,141.6,FALSE
215.1,129.7,129.9,7.4,10.8,141.1,FALSE
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215.5,130.2,130.1,8.9,9.8,142.4,FALSE
215.1,130.3,130.3,9.8,9.5,141.9,FALSE
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214.8,129.7,129.3,8.3,9,142,FALSE
215.2,130.1,129.8,7.9,10.7,141.8,FALSE
214.8,129.7,129.7,8.6,9.1,142.3,FALSE
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215.3,129.9,129.4,7.9,10,142,FALSE
215.3,130.3,130.1,8.5,9.3,142.1,FALSE
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214.4,129.8,129.2,8.9,9.4,142.3,FALSE
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214.8,129.4,129.1,8.2,10.2,141,FALSE
214.3,129.5,129.4,8.3,10.2,141.8,FALSE
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214.5,129,129.6,7.8,9.8,142,FALSE
214.6,129.8,129.4,7.2,10,141.3,FALSE
215.3,130.6,130,9.5,9.7,141.1,FALSE
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215.4,130.2,130.2,7.6,10.9,141.6,FALSE
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215.1,130,129.8,8.2,10.3,141.4,FALSE
215.1,129.6,129.3,8.3,9.9,141.6,FALSE
215.3,129.7,129.4,7.5,10.5,141.5,FALSE
215.4,129.8,129.4,8,10.6,141.5,FALSE
214.5,130,129.5,8,10.8,141.4,FALSE
215,130,129.8,8.6,10.6,141.5,FALSE
215.2,130.6,130,8.8,10.6,140.8,FALSE
214.6,129.5,129.2,7.7,10.3,141.3,FALSE
214.8,129.7,129.3,9.1,9.5,141.5,FALSE
215.1,129.6,129.8,8.6,9.8,141.8,FALSE
214.9,130.2,130.2,8,11.2,139.6,FALSE
213.8,129.8,129.5,8.4,11.1,140.9,FALSE
215.2,129.9,129.5,8.2,10.3,141.4,FALSE
215,129.6,130.2,8.7,10,141.2,FALSE
214.4,129.9,129.6,7.5,10.5,141.8,FALSE
215.2,129.9,129.7,7.2,10.6,142.1,FALSE
214.1,129.6,129.3,7.6,10.7,141.7,FALSE
214.9,129.9,130.1,8.8,10,141.2,FALSE
214.6,129.8,129.4,7.4,10.6,141,FALSE
215.2,130.5,129.8,7.9,10.9,140.9,FALSE
214.6,129.9,129.4,7.9,10,141.8,FALSE
215.1,129.7,129.7,8.6,10.3,140.6,FALSE
214.9,129.8,129.6,7.5,10.3,141,FALSE
215.2,129.7,129.1,9,9.7,141.9,FALSE
215.2,130.1,129.9,7.9,10.8,141.3,FALSE
215.4,130.7,130.2,9,11.1,141.2,FALSE
215.1,129.9,129.6,8.9,10.2,141.5,FALSE
215.2,129.9,129.7,8.7,9.5,141.6,FALSE
215,129.6,129.2,8.4,10.2,142.1,FALSE
214.9,130.3,129.9,7.4,11.2,141.5,FALSE
215,129.9,129.7,8,10.5,142,FALSE
214.7,129.7,129.3,8.6,9.6,141.6,FALSE
215.4,130,129.9,8.5,9.7,141.4,FALSE
214.9,129.4,129.5,8.2,9.9,141.5,FALSE
214.5,129.5,129.3,7.4,10.7,141.5,FALSE
214.7,129.6,129.5,8.3,10,142,FALSE
215.6,129.9,129.9,9,9.5,141.7,FALSE
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214.4,129.7,129.5,8,10.3,141.2,FALSE
215.1,130,129.8,9.1,10.2,141.5,FALSE
214.7,130,129.4,7.8,10,141.2,FALSE
214.4,130.1,130.3,9.7,11.7,139.8,TRUE
214.9,130.5,130.2,11,11.5,139.5,TRUE
214.9,130.3,130.1,8.7,11.7,140.2,TRUE
215,130.4,130.6,9.9,10.9,140.3,TRUE
214.7,130.2,130.3,11.8,10.9,139.7,TRUE
215,130.2,130.2,10.6,10.7,139.9,TRUE
215.3,130.3,130.1,9.3,12.1,140.2,TRUE
214.8,130.1,130.4,9.8,11.5,139.9,TRUE
215,130.2,129.9,10,11.9,139.4,TRUE
215.2,130.6,130.8,10.4,11.2,140.3,TRUE
215.2,130.4,130.3,8,11.5,139.2,TRUE
215.1,130.5,130.3,10.6,11.5,140.1,TRUE
215.4,130.7,131.1,9.7,11.8,140.6,TRUE
214.9,130.4,129.9,11.4,11,139.9,TRUE
215.1,130.3,130,10.6,10.8,139.7,TRUE
215.5,130.4,130,8.2,11.2,139.2,TRUE
214.7,130.6,130.1,11.8,10.5,139.8,TRUE
214.7,130.4,130.1,12.1,10.4,139.9,TRUE
214.8,130.5,130.2,11,11,140,TRUE
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215.1,130.6,130.3,12.3,10.2,139.6,TRUE
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215.1,130.7,130.4,10.5,11.2,139.7,TRUE
214.7,130.5,130.5,9.9,10.3,140.1,TRUE
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215,130.4,130.4,9.4,11.6,140.2,TRUE
215.5,130.7,130.3,10.2,11.8,140,TRUE
215.1,130.2,130.2,10.1,11.3,140.3,TRUE
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214.3,130.2,130,10.7,10.5,139.8,TRUE
214.5,130.2,129.8,12.3,11.2,139.2,TRUE
214.9,130.5,130.2,10.6,11.5,139.9,TRUE
214.6,130.2,130.4,10.5,11.8,139.7,TRUE
214.2,130,130.2,11,11.2,139.5,TRUE
214.8,130.1,130.1,11.9,11.1,139.5,TRUE
214.6,129.8,130.2,10.7,11.1,139.4,TRUE
214.9,130.7,130.3,9.3,11.2,138.3,TRUE
214.6,130.4,130.4,11.3,10.8,139.8,TRUE
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214.7,130,129.4,10.2,11,139.2,TRUE
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214.6,129.7,129.3,10.4,11,139.3,TRUE
214.5,130.1,130.1,12.1,10.3,139.4,TRUE
214.5,130.3,130,11,11.5,139.5,TRUE
215.1,130,130.3,11.6,10.5,139.7,TRUE
214.2,129.7,129.6,10.3,11.4,139.5,TRUE
214.4,130.1,130,11.3,10.7,139.2,TRUE
214.8,130.4,130.6,12.5,10,139.3,TRUE
214.6,130.6,130.1,8.1,12.1,137.9,TRUE
215.6,130.1,129.7,7.4,12.2,138.4,TRUE
214.9,130.5,130.1,9.9,10.2,138.1,TRUE
214.6,130.1,130,11.5,10.6,139.5,TRUE
214.7,130.1,130.2,11.6,10.9,139.1,TRUE
214.3,130.3,130,11.4,10.5,139.8,TRUE
215.1,130.3,130.6,10.3,12,139.7,TRUE
216.3,130.7,130.4,10,10.1,138.8,TRUE
215.6,130.4,130.1,9.6,11.2,138.6,TRUE
214.8,129.9,129.8,9.6,12,139.6,TRUE
214.9,130,129.9,11.4,10.9,139.7,TRUE
213.9,130.7,130.5,8.7,11.5,137.8,TRUE
214.2,130.6,130.4,12,10.2,139.6,TRUE
214.8,130.5,130.3,11.8,10.5,139.4,TRUE
214.8,129.6,130,10.4,11.6,139.2,TRUE
214.8,130.1,130,11.4,10.5,139.6,TRUE
214.9,130.4,130.2,11.9,10.7,139,TRUE
214.3,130.1,130.1,11.6,10.5,139.7,TRUE
214.5,130.4,130,9.9,12,139.6,TRUE
214.8,130.5,130.3,10.2,12.1,139.1,TRUE
214.5,130.2,130.4,8.2,11.8,137.8,TRUE
215,130.4,130.1,11.4,10.7,139.1,TRUE
214.8,130.6,130.6,8,11.4,138.7,TRUE
215,130.5,130.1,11,11.4,139.3,TRUE
214.6,130.5,130.4,10.1,11.4,139.3,TRUE
214.7,130.2,130.1,10.7,11.1,139.5,TRUE
214.7,130.4,130,11.5,10.7,139.4,TRUE
214.5,130.4,130,8,12.2,138.5,TRUE
214.8,130,129.7,11.4,10.6,139.2,TRUE
214.8,129.9,130.2,9.6,11.9,139.4,TRUE
214.6,130.3,130.2,12.7,9.1,139.2,TRUE
215.1,130.2,129.8,10.2,12,139.4,TRUE
215.4,130.5,130.6,8.8,11,138.6,TRUE
214.7,130.3,130.2,10.8,11.1,139.2,TRUE
215,130.5,130.3,9.6,11,138.5,TRUE
214.9,130.3,130.5,11.6,10.6,139.8,TRUE
215,130.4,130.3,9.9,12.1,139.6,TRUE
215.1,130.3,129.9,10.3,11.5,139.7,TRUE
214.8,130.3,130.4,10.6,11.1,140,TRUE
214.7,130.7,130.8,11.2,11.2,139.4,TRUE
214.3,129.9,129.9,10.2,11.5,139.6,TRUE
Exercício 2 Pratico:
Invente um exemplo (se inventar, envie uma copia para gasarrie@usp,br) para aplicar ML Supervisionado para Predição ou Causas e Efeito ou Regressão ou crie uma variável preditora aleatória para pós-venda (de 0 a 100), no arquivo da Satisfação do Cliente, rode no SAS e no Weka, dead line ou due date:17/4/2023:
Dados:
Bu_Unit | Sales | Price | Qu_level | Claims | NPS | PV | Satisfac |
1 | 65,98108 | 97,8022 | 96,77419 | 13,58025 | 98,9011 | 19 | 97,82609 |
2 | 15,8371 | 98,9011 | 98,3871 | 12,34568 | 97,8022 | 29 | 98,91304 |
3 | 8,885232 | 100 | 100 | 11,11111 | 100 | 21 | 100 |
4 | 12,46401 | 98,9011 | 95,16129 | 12,34568 | 96,7033 | 94 | 96,73913 |
5 | 80,66639 | 21,97802 | 19,35484 | 100 | 2,197802 | 34 | 21,73913 |
6 | 32,16783 | 23,07692 | 22,58065 | 97,53086 | 3,296703 | 64 | 23,91304 |
7 | 23,44714 | 24,17582 | 24,19355 | 96,2963 | 2,747253 | 61 | 25 |
8 | 89,96298 | 24,17582 | 19,35484 | 95,06173 | 2,197802 | 25 | 26,08696 |
9 | 31,4274 | 64,83516 | 56,45161 | 50,61728 | 65,93407 | 10 | 65,21739 |
10 | 11,22995 | 65,93407 | 51,6129 | 49,38272 | 71,42857 | 3 | 66,30435 |
11 | 77,45784 | 70,32967 | 53,22581 | 46,91358 | 63,73626 | 56 | 68,47826 |
12 | 23,89963 | 68,13187 | 51,6129 | 45,67901 | 61,53846 | 4 | 67,3913 |
13 | 7,40436 | 86,81319 | 80,64516 | 25,92593 | 90,10989 | 90 | 86,95652 |
14 | 0,287947 | 87,91209 | 79,03226 | 24,69136 | 85,71429 | 48 | 85,86957 |
15 | 83,42246 | 87,91209 | 77,41935 | 22,22222 | 90,10989 | 78 | 88,04348 |
16 | 100 | 86,81319 | 75,80645 | 25,92593 | 84,61538 | 88 | 84,78261 |
| | | | | média= | 724 | |
Arquivo de Dados para o Weka
@RELATION Customer
@ATTRIBUTE U_Neg REAL
@ATTRIBUTE Vendas REAL
@ATTRIBUTE Preco REAL
@ATTRIBUTE Niv_Qual REAL
@ATTRIBUTE Reclama REAL
@ATTRIBUTE NPS REAL
@ATTRIBUTE P_Vend REAL
@ATTRIBUTE Satisf REAL
@DATA
Programa SAS - Ciência de Dados Robusta para Machine Learnic Superv. para Casusas & Efeito
Data Customer;
Input Bu_Unit Sales Price Qu_level Claims NPS P_Vend Satisfac;
Cards;
DADOS
;
proc print;
run;
proc reg;
model Satisfac = Sales Price Qu_level Claims NPS P_Vend ;
Run;
proc robustreg;
model Satisfac = Sales Price Qu_level Claims NPS P_Vend ;
Run;
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