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Published on 18. August 2023
Book
Paperback/Softback
60 pages
978-620-6-26684-6 (ISBN)
Description
Mashinnoe obuchenie w medicine razwiwaetsq kak znachimaq oblast' issledowanij, pozwolqüschaq dawat' prognozy i glubzhe ponimat' medicinskie dannye. Bol'shinstwo metodow mashinnogo obucheniq prqmo ili koswenno zawisqt ot neskol'kih harakteristik, opredelqüschih powedenie algoritma, wliqüschih na wyhod i slozhnost' poluchaemyh modelej. V proshlom mnogie metody mashinnogo obucheniq ispol'zowalis' dlq wyqwleniq serdechno-sosudistyh zabolewanij. Nejronnye seti i logisticheskaq regressiq - odni iz nemnogih populqrnyh metodow mashinnogo obucheniq, ispol'zuemyh w diagnostike serdechno-sosudistyh zabolewanij. Analiziruütsq takie algoritmy, kak mashina opornyh wektorow, K-nearest neighbour, klassifikator Random Forest, a takzhe kombinirowannye podhody, wklüchaüschie wysheupomqnutye algoritmy diagnostiki zabolewanij serdca. Sistema byla realizowana i obuchena na platforme python s ispol'zowaniem modeli mashinnogo obucheniq. Dlq sbora nowyh dannyh frejmwork mozhet byt' rasshiren.
More details
Language
Other
Product notice
Paperback (trade)
Unsewn / adhesive bound
Dimensions
Height: 220 mm
Width: 150 mm
Thickness: 5 mm
Weight
107 gr
ISBN-13
978-620-6-26684-6 (9786206266846)
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Schweitzer Classification
Person
Doktor S.Ramacharan rabotaet professorom kafedry informacionnyh tehnologij w Institute tehnologij i nauki imeni G. Naraqnammy, Hajdarabad, Indiq, s opytom prepodawaniq bolee 25 let. Okonchil bakalawriat po CSE (1997), magistraturu po CSE (2007) i doktoranturu po CSE (2017). Specializiruetsq w takih oblastqh, kak SE, SUBD, NP, DM i dr,