Victor Boyarshinov: Machine Learning In Computational Finance - Paperback
ISBN: 9783659118890
Paperback, [PU: LAP Lambert Academic Publishing], In the first part of the book practical algorithms for building optimal trading strategies are constructed. Both non-restricted and risk-… More...
Paperback, [PU: LAP Lambert Academic Publishing], In the first part of the book practical algorithms for building optimal trading strategies are constructed. Both non-restricted and risk-adjusted (Sterling ratio and Sharp ratio) trading strategies are considered. Constructed optimal trading strategies can be used as training dataset for the AI application. In the next part of the book one particular type of Machine Learning - finding optimal linear separators - is considered, and combinatorial deterministic algorithm for computing minimum linear separator set in 2 dimensions is given. In the last part of the book presented efficient algorithms for preventing overfitting. Shape constrained regression is an accepted methodology to deal with overfitting. Algorithms for nonparametric shape constrained regression in the form of isotonic and unimodal regressions are given., Business & Management<
Victor Boyarshinov: Machine Learning In Computational Finance: Practical algorithms for building artificial intelligence applications - used book
2012, ISBN: 9783659118890
2012-04-09. Good. Ships with Tracking Number! INTERNATIONAL WORLDWIDE Shipping available. May not contain Access Codes or Supplements. May be re-issue. May be ex-library. Shippin… More...
2012-04-09. Good. Ships with Tracking Number! INTERNATIONAL WORLDWIDE Shipping available. May not contain Access Codes or Supplements. May be re-issue. May be ex-library. Shipping & Handling by region. Buy with confidence, excellent customer service!, 2012-04-09, 2.5<
Machine Learning In Computational Finance - Paperback
ISBN: 9783659118890
Paperback, [PU: LAP Lambert Academic Publishing], In the first part of the book practical algorithms for building optimal trading strategies are constructed. Both non-restricted and risk-… More...
Paperback, [PU: LAP Lambert Academic Publishing], In the first part of the book practical algorithms for building optimal trading strategies are constructed. Both non-restricted and risk-adjusted (Sterling ratio and Sharp ratio) trading strategies are considered. Constructed optimal trading strategies can be used as training dataset for the AI application. In the next part of the book one particular type of Machine Learning - finding optimal linear separators - is considered, and combinatorial deterministic algorithm for computing minimum linear separator set in 2 dimensions is given. In the last part of the book presented efficient algorithms for preventing overfitting. Shape constrained regression is an accepted methodology to deal with overfitting. Algorithms for nonparametric shape constrained regression in the form of isotonic and unimodal regressions are given., Business & Management<
Machine Learning In Computational Finance: Practical algorithms for building artificial intelligence applications - used book
2012, ISBN: 9783659118890
2012-04-09. Good. Ships with Tracking Number! INTERNATIONAL WORLDWIDE Shipping available. May not contain Access Codes or Supplements. May be re-issue. May be ex-library. Shippin… More...
2012-04-09. Good. Ships with Tracking Number! INTERNATIONAL WORLDWIDE Shipping available. May not contain Access Codes or Supplements. May be re-issue. May be ex-library. Shipping & Handling by region. Buy with confidence, excellent customer service!, 2012-04-09, 2.5<
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In the first part of the book practical algorithms for building optimal trading strategies are constructed. Both non-restricted and risk-adjusted (Sterling ratio and Sharp ratio) trading strategies are considered. Constructed optimal trading strategies can be used as training dataset for the AI application. In the next part of the book one particular type of Machine Learning - finding optimal linear separators - is considered, and combinatorial deterministic algorithm for computing minimum linear separator set in 2 dimensions is given. In the last part of the book presented efficient algorithms for preventing overfitting. Shape constrained regression is an accepted methodology to deal with overfitting. Algorithms for nonparametric shape constrained regression in the form of isotonic and unimodal regressions are given.
Details of the book - Machine Learning In Computational Finance: Practical algorithms for building artificial intelligence applications
EAN (ISBN-13): 9783659118890 ISBN (ISBN-10): 3659118893 Hardcover Paperback Publishing year: 2012 Publisher: LAP LAMBERT Academic Publishing
Book in our database since 2008-08-13T16:53:50+01:00 (London) Detail page last modified on 2024-01-31T13:42:07+00:00 (London) ISBN/EAN: 3659118893
ISBN - alternate spelling: 3-659-11889-3, 978-3-659-11889-0 Alternate spelling and related search-keywords: Book title: machine learning, applications finance
