Support vector machines: theory and applications /

Support vector machines: theory and applications /

Bibliografiske detaljer
Andre forfattere:	Wang, Lipo
Format:	Bog
Sprog:	English
Udgivet:	Berlin : Springer, 2005.
Serier:	Studies in fuzziness and soft computing, volume 177
Fag:	Support vector machines. Data mining. Computer science. Pattern recognition systems.
Classic Catalogue:	View this record in Classic Catalogue

Lignende værker

An introduction to support vector machines : and other kernel-based learning methods /
af: Cristianini, Nello
Udgivet: (2000)

Pattern classification /
af: Duda, Richard O.

A machine learning approach to detect depression and anxiety using supervised learning
af: Ullas, Md Tahmidur Rahman, et al.
Udgivet: (2019)

Pattern recognition with Quantum Support Vector Machine(QSVM) on near term quantum processors.
af: Ahmed, Sajjad
Udgivet: (2019)

Prediction of Epileptic Seizures using digital signal processing and support vector machine
af: Siddique, Nusayer Masud, et al.
Udgivet: (2021)

Detection of epileptic seizure using Support Vector Machine Classifier - extracted features from EEG signals
af: Amiz, Asef Hassan, et al.
Udgivet: (2021)

Aspect based opinion mining on restaurant reviews
af: Tonmoy, Sazid Hasan, et al.
Udgivet: (2024)

Supervising vehicle using pattern recognition
af: Lushan, Mihodi Hasan, et al.
Udgivet: (2018)

Handwritten Bangla character recognition to braille pattern conversion using image processing and machine learning
af: Abir, Tawhidur Rahman, et al.
Udgivet: (2019)

Phase Transitions in Machine Learning
af: Lorenza Saitta, Attilio Giordana, Antoine Cornuéjols
Udgivet: (2012)

Yield prediction for precision agriculture using extreme gradient boosting and support vector regression
af: Ahmed, Md. Sabbir, et al.
Udgivet: (2021)

Decision support systems in the 21st century /
af: Marakas, George M.
Udgivet: (2003)

Decision support systems in the twenty-first century /
af: Marakas, George M.
Udgivet: (1999)

Scaling Up Machine Learning
af: Edited by Ron Bekkerman, Mikhail Bilenko, John Langford
Udgivet: (2012)

Data analysis on the Bangladesh share market using Machine-Learning
af: Sadman, Syed Hassan, et al.
Udgivet: (2021)

Detecting Adverse Drug Reaction (ADR) with data mining and predicting its intensity with machine learning
af: Hussain, Nadib, et al.
Udgivet: (2018)

Understanding machine learning : from theory to algorithms /
af: Shalev-Shwartz, Shai
Udgivet: (2014)

Where will you setup your business next?: a machine learning approach to suggest ideal geographical location for new restaurant establishment
af: Shihab, Ibne Farabi, et al.
Udgivet: (2018)

Study on human emotion based on facial expressions through human machine communication
af: Murshed, Tahmin Aysha, et al.
Udgivet: (2021)

Foundations of machine learning /
af: Mohri, Mehryar, et al.
Udgivet: (2018)

Gene classification and pattern analysis using data mining and machine learning techniques
af: Ramisa, Aiman Jabeen, et al.
Udgivet: (2021)

Grouping of handwritten Bangla basic characters, numerals and vowel modifiers for multilayer classification
af: Reza, Khondker Nayef, et al.
Udgivet: (2017)

Detection of fake identities on twitter using supervised machine learning
af: Rahman, MD. Takiur, et al.
Udgivet: (2019)

Performance analysis of machine learning classi ers for detecting PE malware
af: Azmee, ABM.Adnan, et al.
Udgivet: (2020)

Predicting depression in Bangladeshi undergraduates using machine learning
af: Choudhury, Ahnaf Atef, et al.
Udgivet: (2019)

A new approach to select adaptive Intrinsic Mode Functions (IMFs) of Empirical Mode Decomposition (EMD)
af: Sultana Nishi, Razia, et al.
Udgivet: (2016)

Cyberbullying detection using sentiment analysis in social media
af: Sintaha, Mifta, et al.
Udgivet: (2016)

Credit card fraud detection using machine learning techniques
af: Kabir, Tasmia, et al.
Udgivet: (2021)

Pattern recognition and machine learning /
af: Bishop, Christopher M.
Udgivet: (2006)

Vector calculus /
af: Colley, Susan Jane
Udgivet: (2012)

A new pattern recognition method for abnormal event detection in crowded scenarios
af: Mostafa, Tahjid Ashfaque
Udgivet: (2017)

The Data Science Design Manual /
af: Skiena, Steven S.
Udgivet: (2017)

Neural networks for pattern recognition /
af: Bishop, Christopher M.
Udgivet: (1995)

Comparative study of toxic comments classification using machine learning algorithms
af: Razzak, Razia, et al.
Udgivet: (2021)

Schaum's outline of theory and problems of vector analysis and an introduction to tensor analysis /
af: Spiegel, Murray R.
Udgivet: (1974)

A machine learning approach to predict young voter enthusiasm based on non-political factors
af: Rahman, Md. Nowroz Junaed, et al.
Udgivet: (2021)

Market basket analysis for improving the effectiveness of marketing and sales using Apriori, FP Growth and Eclat Algorithm
af: Khan, Mohammod Akib, et al.
Udgivet: (2017)

Travel time prediction using machine learning and weather impact on traffic conditions
af: Deb, Bilash, et al.
Udgivet: (2018)

Deep learning /
af: Goodfellow, Ian
Udgivet: (2016)

Handwritten character recognition and prediction of age, gender and handedness using machine learning
af: Al Emran, Md., et al.
Udgivet: (2018)