DATA MINING techniques. PREDICTIVE MODELS with SAS Enterprise Miner

DATA MINING techniques. PREDICTIVE MODELS with SAS Enterprise Miner

by Scientific Books

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Overview

DATA MINING techniques. PREDICTIVE MODELS with SAS Enterprise Miner by Scientific Books

SAS Institute implements data mining in Enterprise Miner software, which will be used in this book focused predictive models. SAS Institute defines the concept of Data Mining as the process of selecting (Selecting), explore (Exploring), modify (Modifying), modeling (Modeling) and rating (Assessment) large amounts of data with the aim of uncovering unknown patterns which can be used as a comparative advantage with respect to competitors. This process is summarized with the acronym SEMMA which are the initials of the 5 phases which comprise the process of Data Mining according to SAS Institute. The essential content of the book is as follows:

SAS ENTERPRISE MINER WORKING ENVIRONMENT
MODELLING PREDICTIVE TECHNIQUES WITH SAS ENTERPRISE MINER
REGRESSION NODE: MULTIPLE REGRESSION MODEL
LOGISTIC REGRESSION
DMINE REGRESSION NODE
PARTIAL LEAST SQUARES NODE. PLS REGRESSION
LARS NODE
CLASSIFICATION PREDICTIVE TECHNIQUES. DECISION TREES WITH SAS ENTERPRISE MINER
DECISION TREE NODE
PREDICTIVE MODELS WITH NEURAL NETWORKS WITH SAS ENTERPRISE MINER
OPTIMIZATION AND ADJUSTMENT OF MODELS WITH NETS: NEURAL NETWORK NODE
SIMPLE NEURAL NETWORKS
PERCEPTRONS
HIDDEN LAYERS
MULTILAYER PERCEPTRONS (MLPS)
RADIAL BASIS FUNCTION (RBF) NETWORKS
SCORING
AUTONEURAL NODE
NETWORK ARCHITECTURES
NEURAL NODE
TWOSTAGE NODE
GRADIENT BOOSTING NODE
MEMORY-BASED REASONING (MBR) NODE
RULE INDUCTION NODE
ENSEMBLE NODE
COMBINING MODELS USING THE ENSEMBLE NODE
MODEL IMPORT NODE
SVM NODE
ASSESS PHASE IN DATA MINING PROCESS
CUTOFF NODE
DECISIONS NODE
MODEL COMPARISON NODE
SCORE NODE

Product Details

ISBN-13: 9781512100037
Publisher: CreateSpace Publishing
Publication date: 05/08/2015
Pages: 332
Product dimensions: 7.00(w) x 10.00(h) x 0.69(d)

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