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Redes Neurais Artificiais

Rede Neural Multicamadas Feed-forward

Back-propagation

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Projetos RNA Multicamadas Back-propagation

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Choose your exploratory data set that contains data and labels of the class

elements. Train an MLP neural network with the backpropagation algorithm,

using 75% of the data examples for training and the remaining 25% for testing.

1.Explore the correlation between the learning rate and momentum and the

speed of training when a training error of 0.001 is chosen to stop the

training process. For example, use different values such as:

i.Learning rate 0.1, momentum 0.5

ii.Learning rate 0.5, momentum 0.5iii.Learning rate 0.5, momentum 0.9

iv.Learning rate 0.5, momentum 0.1

Which values for the learning rate and momentum do you think are the best

for your neural network?

2.Explore the influence of the number of hidden nodes and number of layers

on the training and test error and on the time for training.

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For example, you can use one of the following problems for the project:

Iris Classification

The Smoker and the Risk of Cancer Gas Consumption Prediction

Handwritten Characters Recognition

Bank Loan Decision

Inverted Pendulum

Medical Diagnosis Mortgage approval

Traveling Salesman

Resource Scheduling

Unemployment prediction

Musical signals-to-notes transformation Playing ticktacktoe

Predicting beer sales

Stock Market Prediction

Water Flow to a Sewage Plant Prediction

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Reconhecimento de Caracteres Escritos Mo

variabilidade de formas em que o nmero 3 pode ser escrito

padropode ser representado por um conjunto de

aspectos: curvas, linhas retas,pontos, cor, ...

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Classificao da Iris

150 amostras em trs classes: setosa,versicolorevirginica

4 atributos, medidos em centmetros, para cada amostra:

comp. sepal, comp. petal, larg. sepale larg. petal.

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SL - comprimento sepal, PL - comprimento petal

SW - largura sepal, PW - largura petal

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Classificao Solos

seis tipos de solos, cada solo caracterizado

por diferentes concentraes de ions

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Previso Consumo de Gs

X meses jan, abr, out dos anos 88-91

Y1consumo de gs (gallons per capita)

Y2

temperatura mnima mdia (0

C)

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Diagnstico Mdico Baseado em Exemplos

Case Sex Age Lumbar pain Spinal column stiffness

1 Male 30 yes yes

2 Women 23 not not

3 Male 30 not not

4 Male 70 not not

5 Women 63 not not

6 Male 59 not not

7 Women 61 not not

. . .

.

.

.

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Diagnstico Mdico Baseado em Regras

4 regras envolvendo 4 manifestaes e 4 diagnsticos

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Controle do Pndulo Invertido

Y fora aplicada no carro para frente e para trs

ngulo do pndulo com a vertical

velocidade angular

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