Data Mining Algorithms in C++ Data Patterns and Algorithms for Modern Applications /

Find the various relationships among variables that can be present in big data as well as other data sets. This book also covers information entropy, permutation tests, combinatorics, predictor selections, and eigenvalues to give you a well-rounded view of data mining and algorithms in C++. Furtherm...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριος συγγραφέας: Masters, Timothy (Συγγραφέας, http://id.loc.gov/vocabulary/relators/aut)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Berkeley, CA : Apress : Imprint: Apress, 2018.
Έκδοση:1st ed. 2018.
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
LEADER 03401nam a2200553 4500
001 978-1-4842-3315-3
003 DE-He213
005 20191025032512.0
007 cr nn 008mamaa
008 171218s2018 xxu| s |||| 0|eng d
020 |a 9781484233153  |9 978-1-4842-3315-3 
024 7 |a 10.1007/978-1-4842-3315-3  |2 doi 
040 |d GrThAP 
050 4 |a QA76.7-76.73 
050 4 |a QA76.76.C65 
072 7 |a UMX  |2 bicssc 
072 7 |a COM051010  |2 bisacsh 
072 7 |a UMX  |2 thema 
072 7 |a UMC  |2 thema 
082 0 4 |a 005.13  |2 23 
100 1 |a Masters, Timothy.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
245 1 0 |a Data Mining Algorithms in C++  |h [electronic resource] :  |b Data Patterns and Algorithms for Modern Applications /  |c by Timothy Masters. 
250 |a 1st ed. 2018. 
264 1 |a Berkeley, CA :  |b Apress :  |b Imprint: Apress,  |c 2018. 
300 |a XIV, 286 p.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
347 |a text file  |b PDF  |2 rda 
505 0 |a 1. Information and Entropy -- 2. Screening for Relationships -- 3. Displaying Relationship Anomalies -- 4. Fun With Eigenvectors -- 5. Using the DATAMINE Program. 
520 |a Find the various relationships among variables that can be present in big data as well as other data sets. This book also covers information entropy, permutation tests, combinatorics, predictor selections, and eigenvalues to give you a well-rounded view of data mining and algorithms in C++. Furthermore, Data Mining Algorithms in C++ includes classic techniques that are widely available in standard statistical packages, such as maximum likelihood factor analysis and varimax rotation. After reading and using this book, you'll come away with many code samples and routines that can be repurposed into your own data mining tools and algorithms toolbox. This will allow you to integrate these techniques in your various data and analysis projects. You will: Discover useful data mining techniques and algorithms using the C++ programming language Carry out permutation tests Work with the various relationships and screening types for these relationships Master predictor selections Use the DATAMINE program . 
650 0 |a Programming languages (Electronic computers). 
650 0 |a Big data. 
650 0 |a Data mining. 
650 0 |a Computer programming. 
650 0 |a Algorithms. 
650 1 4 |a Programming Languages, Compilers, Interpreters.  |0 http://scigraph.springernature.com/things/product-market-codes/I14037 
650 2 4 |a Big Data.  |0 http://scigraph.springernature.com/things/product-market-codes/I29120 
650 2 4 |a Data Mining and Knowledge Discovery.  |0 http://scigraph.springernature.com/things/product-market-codes/I18030 
650 2 4 |a Programming Techniques.  |0 http://scigraph.springernature.com/things/product-market-codes/I14010 
650 2 4 |a Algorithms.  |0 http://scigraph.springernature.com/things/product-market-codes/M14018 
710 2 |a SpringerLink (Online service) 
773 0 |t Springer eBooks 
776 0 8 |i Printed edition:  |z 9781484233146 
776 0 8 |i Printed edition:  |z 9781484233160 
776 0 8 |i Printed edition:  |z 9781484247112 
856 4 0 |u https://doi.org/10.1007/978-1-4842-3315-3  |z Full Text via HEAL-Link 
912 |a ZDB-2-CWD 
950 |a Professional and Applied Computing (Springer-12059)