IBM SPSS Modeler cookbook : over 60 practical recipes to achieve better results using the experts' methods for data mining /: over 60 practical recipes to achieve better results using the experts' methods for data mining. (2013)

• Record Type: Book
• Other Titles: SPSS Modeler cookbook
• Further Information: Note: Keith McCormick [and others] ; foreword by Colin Shearer.
• Other Names: McCormick, Keith
• Contents: Cover; Copyright; Credits; Foreword; About the Authors; About the Reviewers; www.PacktPub.com; Table of Contents; Preface; Chapter 1: Data Understanding; Introduction; Using an empty aggregate to evaluate sample size; Evaluating the need to sample from the initial data; Using CHAID stumps when interviewing an SME; Using a single cluster K-means as an alternative to anomaly detection; Using an @NULL multiple Derive to explore missing data; Creating an outlier report to give to SMEs; Detecting potential model instability early using the Partition node and Feature Selection. Chapter 2: Data Preparation -- SelectIntroduction; Using the Feature Selection node creatively to remove, or decapitate, perfect predictors; Running a Statistics node on anti-join to evaluate potential missing data; Evaluating the use of sampling for speed; Removing redundant variables using correlation matrices; Selecting variable using the CHAID modeling node; Selecting variables using the Means node; Selecting variables using single-antecedent association rules; Chapter 3: Data Preparation -- Clean; Introduction; Binning scale variables to address missing data. Using a full data model/partial data model approach to address missing dataImputing in-stream mean or median; Imputing missing values randomly from uniform or normal distributions; Using random imputation to match a variable's distribution; Searching for similar records using a neural network for inexact matching; Using neuro-fuzzy searching to find similar names; Producing longer Soundex codes; Chapter 4: Data Preparation -- Construct; Introduction; Building transformations with multiple Derive nodes; Calculating and comparing conversion rates; Grouping categorical values. Transforming high skew and kurtosis variables with a multiple Derive nodeCreating flag variables for aggregation; Using Association Rules for interaction detection/feature creation; Creating time-aligned cohorts; Chapter 5: Data Preparation -- Integrate and Format; Introduction; Speeding up merge with caching and optimization settings; Merging a look-up table; Shuffle-down (nonstandard aggregation); Cartesian product merge using key-less merge by key; Multiplying out using Cartesian product merge, user source, and derive dummy; Changing large numbers of variable names without scripting. Parsing nonstandard datesParsing and performing a conversion on a complex stream; Sequence processing; Chapter 6: Selecting and Building a Model; Introduction; Evaluating balancing with the Auto Classifier; Building models with and without outliers; Neural Network Feature Selection; Creating a bootstrap sample; Creating bagged logistic regression models; Using KNN to match similar cases; Using Auto Classifier to tune models; Next-Best-Offer for large datasets; Chapter 7: Modeling -- Assessment, Evaluation, Deployment, and Monitoring; Introduction; How (and why) to validate as well as test.
• Publisher Details: Birmingham, UK : Packt Pub
• Publication Date: 2013
• Extent: 1 online resource (1 volume), illustrations
• Subjects: 006.312; COMPUTERS -- Databases -- Data Mining; Data mining; Data mining; COMPUTERS -- General; Data mining; Data mining; COMPUTERS -- Enterprise Applications -- General; Electronic books
• Languages: English
• ISBNs: 9781849685474; 1849685479; 1849685460; 9781849685467
• Related ISBNs: 9781849685467
• Notes: Note: Online resource; title from cover (Safari, viewed Jan. 16, 2014).; Note: Print version record.
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
• Access Usage: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.