
Ensemble Modelling for Disease Forecasting
LAP Lambert Academic Publishing
Published on 19. June 2020
Book
Paperback/Softback
60 pages
978-620-2-67139-2 (ISBN)
Description
The world is filled with lots and lots of data. Be it data in the form of pictures, statistical values, videos, music, words, etc. Traditionally human being is able to recognize and extract a meaningful pattern out of such data. But as the volume of data increases, it becomes impossible for a human being to extract it meaningfully. To get a meaning out of such bulk data, a set of tools are required with the help of which a machine can be taught to recognize the pattern and extract the information. The term machine learning came into existence. Time is an importantfactor when it comes to data where the sudden change in the values at a particular time can have a huge impact on the outcome. Smart forecasting tools powered by data science is necessary to successfully deal with capacity and strategic planning which is required to handle the scenario and save lives. The purpose of this book is to present an efficient model that can forecast the values more accurately in a particular field.
More details
Language
English
Product notice
Paperback (trade)
Unsewn / adhesive bound
Dimensions
Height: 220 mm
Width: 150 mm
Thickness: 5 mm
Weight
107 gr
ISBN-13
978-620-2-67139-2 (9786202671392)
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Schweitzer Classification
Persons
Dr. Nonita Sharma works in the domain of Time series forecasting, Data Analytics, Wireless Sensor Networks.Dr. Deepti Kakkar's area of interest includes Spectrum Sensing in Multihop Networks for Cognitive Radios. Nashreen Sultana works in the area of time series forecasting modelling.