segunda-feira, 13 de março de 2023

Exercícios Práticos

 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

214.6,129.7,129.7,8.1,9.5,141.7,FALSE

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

215.2,130.8,129.6,7.9,10.8,141.4,FALSE

214.7,129.7,129.7,7.7,10.9,141.7,FALSE

215.1,129.9,129.7,7.7,10.8,141.8,FALSE

214.5,129.8,129.8,9.3,8.5,141.6,FALSE

214.6,129.9,130.1,8.2,9.8,141.7,FALSE

215,129.9,129.7,9,9,141.9,FALSE

215.2,129.6,129.6,7.4,11.5,141.5,FALSE

214.7,130.2,129.9,8.6,10,141.9,FALSE

215,129.9,129.3,8.4,10,141.4,FALSE

215.6,130.5,130,8.1,10.3,141.6,FALSE

215.3,130.6,130,8.4,10.8,141.5,FALSE

215.7,130.2,130,8.7,10,141.6,FALSE

215.1,129.7,129.9,7.4,10.8,141.1,FALSE

215.3,130.4,130.4,8,11,142.3,FALSE

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

215.1,130,130,7.4,10.5,141.8,FALSE

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

215,130,129.6,7.7,10.5,140.7,FALSE

215.6,130.4,130.1,8.4,10.3,141,FALSE

215.9,130.4,130,8.9,10.6,141.4,FALSE

214.6,130.2,130.2,9.4,9.7,141.8,FALSE

215.5,130.3,130,8.4,9.7,141.8,FALSE

215.3,129.9,129.4,7.9,10,142,FALSE

215.3,130.3,130.1,8.5,9.3,142.1,FALSE

213.9,130.3,129,8.1,9.7,141.3,FALSE

214.4,129.8,129.2,8.9,9.4,142.3,FALSE

214.8,130.1,129.6,8.8,9.9,140.9,FALSE

214.9,129.6,129.4,9.3,9,141.7,FALSE

214.9,130.4,129.7,9,9.8,140.9,FALSE

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

214.8,129.9,129.7,8.3,10.2,141.5,FALSE

214.8,129.9,129.7,7.3,10.9,142,FALSE

214.6,129.7,129.8,7.9,10.3,141.1,FALSE

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

214.5,130.1,130,7.8,10.9,140.9,FALSE

215.4,130.2,130.2,7.6,10.9,141.6,FALSE

214.5,129.4,129.5,7.9,10,141.4,FALSE

215.2,129.7,129.4,9.2,9.4,142,FALSE

215.7,130,129.4,9.2,10.4,141.2,FALSE

215,129.6,129.4,8.8,9,141.1,FALSE

215.1,130.1,129.9,7.9,11,141.3,FALSE

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

215,130.4,130.3,9.1,10.2,141.1,FALSE

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

214.4,130.2,129.9,10.1,12,139.2,TRUE

214.8,130.3,130.4,10.1,12.1,139.6,TRUE

215.1,130.6,130.3,12.3,10.2,139.6,TRUE

215.3,130.8,131.1,11.6,10.6,140.2,TRUE

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

214.9,130,130.3,10.2,11.4,139.6,TRUE

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

214.5,130.2,130.6,9.8,12.1,139.9,TRUE

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

214.5,130.5,130.2,11.8,10.2,139.6,TRUE

214.8,130.2,130.3,10,11.9,139.3,TRUE

214.7,130,129.4,10.2,11,139.2,TRUE

214.6,130.2,130.4,11.2,10.7,139.9,TRUE

215,130.5,130.4,10.6,11.1,139.9,TRUE

214.5,129.8,129.8,11.4,10,139.3,TRUE

214.9,130.6,130.4,11.9,10.5,139.8,TRUE

215,130.5,130.4,11.4,10.7,139.9,TRUE

215.3,130.6,130.3,9.3,11.3,138.1,TRUE

214.7,130.2,130.1,10.7,11,139.4,TRUE

214.9,129.9,130,9.9,12.3,139.4,TRUE

214.9,130.3,129.9,11.9,10.6,139.8,TRUE

214.6,129.9,129.7,11.9,10.1,139,TRUE

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;



Exercício 3 Pratico: 
Crie um blog e coloque todos os exercícios práticos e teóricos.
Enviar o link para o e-mail de exercícios.

Exercício 4 Pratico: 
Crie um site e coloque seu curriculum nele.
Enviar o link para o e-mail de exercícios.



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