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Mãos à Obra: Aprendizado de Máquina com Scikit-Learn e TensorFlow
book

Mãos à Obra: Aprendizado de Máquina com Scikit-Learn e TensorFlow

by Aurélien Géron
March 2019
Intermediate to advanced
576 pages
20h 51m
Portuguese (Portugal, Brazil)
Alta Books
Content preview from Mãos à Obra: Aprendizado de Máquina com Scikit-Learn e TensorFlow
144 | Capítulo 4: Treinando Modelos
flores além da linha superior direita têm mais de 90% de chance de serem Iris-Virginica,
de acordo com o modelo.
Não Iris-Virginica
Comprimento da tala
Iris-Virginica
Largura da Pétala
Figura 4-24. Fronteiras de decisão linear
Assim como outros modelos lineares, os modelos de Regressão Logística podem ser regulari-
zados usando as penalidades ℓ
1
ou ℓ
2
. O Scitkit-Learn adiciona uma penalidade ℓ
2
por padrão.
O hiperparâmetro que controla a força de regularização de um mo-
delo LogisticRegression do Scikit-Learn não é alfa (como em
outros modelos lineares), mas seu inverso: C. Quanto maior o valor
de C, menos o modelo ...
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Publisher Resources

ISBN: 9788550803814