Machine Learning Techniques for Time Series Classification - Michael Botsch
-25% koodilla BOOKS
Toimitus 15-21 arkipäivässä
30 päivän palautusoikeus
Classification of time series is an important task in various fields, e.g., medicine, finance, and industrial applications. This work discusses strong temporal classification using machine learning techniques. Here, two problems must be solved: the detection of those time instances when the class labels change and the correct assignment of the labels. For this purpose the scenario-based random forest algori ... Täydellinen kuvaus
Saatat myös pitää
TOP
INCOSE Systems Engineering Handbook
-25% koodilla BOOKS
Toimittajalla varastossa
TOP
If Anyone Builds It, Everyone Dies: The Case Against Superintelligent AI
Eliezer Yudkowsky, Nate Soares
-25% koodilla BOOKS
Toimittajalla varastossa
TOP
Open Circuits: The Inner Beauty of Electronic Components
Eric Schlaepfer, Windell Oskay
-25% koodilla BOOKS
Toimittajalla varastossa
TOP
Get started with MicroPython on Raspberry Pi Pico: The Official Raspberry Pi Pico Guide
-25% koodilla BOOKS
Toimittajalla varastossa
TOP
Practical Electronics for Inventors
-25% koodilla BOOKS
Toimittajalla varastossa
TOP
Nucleo Boards Programming with the STM32CubeIDE: Hands-on in more than 50 projects
-25% koodilla BOOKS
Toimittajalla varastossa
TOP
Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control
Steven L. Brunton, J. Nathan Kutz
-25% koodilla BOOKS
Toimittajalla varastossa
TOP
Fundamentals of Aerodynamics ISE
Christopher Cadou, John D. Anderson
-25% koodilla BOOKS
Toimittajalla varastossa
TOP
Black Holes: The Key to Understanding the Universe
-25% koodilla BOOKS
Toimittajalla varastossa
TOP
KiCad Like A Pro - Fundamentals and Projects: Getting started with the world's best open-source PCB tool
-25% koodilla BOOKS
Toimittajalla varastossa
TOP
How To Read Water: Clues & Patterns from Puddles to the Sea
-25% koodilla BOOKS
Toimittajalla varastossa
TOP
Foundations of Flavor: The Noma Guide to Fermentation: Including Step-By-Step Information on Making and Cooking with: Koji, Kombuchas, Shoyus, Misos, Vinegars, Garums, Lacto-Ferments and black Fruits Vegetables
-25% koodilla BOOKS
Toimittajalla varastossa
TOP
Make: Electronics: Learning by Discovery: A hands-on primer for the new electronics enthusiast
-25% koodilla BOOKS
Toimittajalla varastossa
TOP
The Idea Factory: Bell Labs and the Great Age of American Innovation
-25% koodilla BOOKS
Toimittajalla varastossa
TOP
Flowers For Algernon: A Modern Literary Classic
-25% koodilla BOOKS
Toimittajalla varastossa
TOP
Professional SMD Assembly: Practical Low-Cost Methods for Reliable PCB Production
-25% koodilla BOOKS
Toimittajalla varastossa
TOP
Blood in the Machine: The Origins of the Rebellion Against Big Tech
-25% koodilla BOOKS
Toimittajalla varastossa
Kuvaus
Classification of time series is an important task in various fields, e.g., medicine, finance, and industrial applications. This work discusses strong temporal classification using machine learning techniques. Here, two problems must be solved: the detection of those time instances when the class labels change and the correct assignment of the labels. For this purpose the scenario-based random forest algorithm and a segment and label approach are introduced. The latter is realized with either the augmented dynamic time warping similarity measure or with interpretable generalized radial basis function classifiers. The main application presented in this work is the detection and categorization of car crashes using machine learning. Depending on the crash severity different safety systems, e.g., belt tensioners or airbags must be deployed at time instances when the best-possible protection of passengers is assured.
Lisätietoja
| Kirjoittaja | Michael Botsch |
|---|---|
| Julkaisija | Cuvillier |
| Julkaisuvuosi | 2023 |
| Kannen tyyppi | Pehmeäkantinen |
| EAN | 9783736978133 |