March 2016
Intermediate to advanced
408 pages
12h 50m
Portuguese (Portugal, Brazil)
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CAPÍTULO 4
Ajustando um Modelo aos Dados
Conceitos fundamentais: Encontrando parâmetros “ideais” de modelos com base nos dados; Escolhendo a meta para mineração de dados; Funções objetivas; Funções de perda.
Técnicas exemplares: Regressão linear; Regressão logística; Máquinas de vetores de suporte.
Como vimos, modelagem preditiva envolve encontrar um modelo da variável alvo em termos de outros atributos descritivos. No Capítulo 3, construímos um modelo de segmentação supervisionada, buscando de forma recursiva atributos informativos em subconjuntos cada vez mais precisos dentro de conjuntos de todos os exemplos, ou a partir da perspectiva geométrica, sub-regiões cada vez mais precisas do espaço do caso. A partir dos dados, produzimos a estrutura ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.