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Browsing by Subject "Decision trees"

Browsing by Subject "Decision trees"

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  • A Comprehensive Study of Data Mining Techniques in Health-care, Medical, and Bioinformatics 
    Mia, Md. Robel; Hossain, Syed Akhter; Chhoton, Amit Chakraborty; Chakraborty, Narayan Ranjan (IEEE, 2018-09-20)
    Data mining and Data warehousing is an imperative part of explore and is realistically worn in diverse domains resembling funding, quantifiable research, teaching, retail, e-business, marketing, health care etc. Many ...
  • Expert Cancer Model Using Supervised Algorithms with a Lasso Selection Approach 
    Ghosh, Pronab; Karim, Asif; Atik, Syeda Tanjila; Afrin, Saima; Saifuzzaman, Mohd. (International Journal of Electrical and Computer Engineering (IJECE), 2021)
    One of the most critical issues of the mortality rate in the medical field in current times is breast cancer. Nowadays, a large number of men and women is facing cancer-related deaths due to the lack of early diagnosis ...
  • Hotel Review Analysis for the Prediction of Business Using Deep Learning Approach 
    Hossen, Md.Sagar; Jony, Anik Hassan; Tabassum, Tasfia; Islam, Md. Tanvir; Rahman, Md Mahfujur; Khatun, Tania (IEEE, 2021-04-12)
    Sentiment analysis is a widely used topic in Natural Language Processing that allows identifying the opinions or sentiments from a given text. Social media is the scope for the customers to share their opinion over the ...
  • Improving Classification Model's Performance Using Linear Discriminant Analysis on Linear Data 
    Ghosh, Joyoshree; Shuvo, Shaon Bhatta (10th International Conference on Computing, Communication and Networking Technologies, ICCCNT 2019, IEEE, 2019)
    Classification is a supervised learning technique for predicting the class of given data points. Before doing classification, it is essential to build a classification model using classification algorithms. There are several ...
  • Machine Learning Applied to Kidney Disease Prediction 
    Rabby, A.K.M. Shahariar Azad; Mamata, Rezwana; Laboni, Monira Akter; Ohidujjaman; Abujar, Sheikh (10th International Conference on Computing, Communication and Networking Technologies, ICCCNT 2019, IEEE, 2019-12-30)
    Machine learning has earned a remarkable position in healthcare sector because of its capability to enhance the disease prediction in healthcare sector. Artificial intelligence and Machine learning techniques are being ...
  • Parametric Study of Student Learning in IT Using Data Mining to Improve Academic Performance 
    Islam, Rubyeat; Sazid, Muhammad Tawsif; Mahmud, Sharifa Rania; Ferdous, Chowdhury Nawrin; Reza, Reshad; Hossain, Syed Akhter (2019 Joint 8th International Conference on Informatics, Electronics and Vision, ICIEV 2019 and 3rd International Conference on Imaging, Vision and Pattern Recognition, icIVPR 2019 with International Conference on Activity and Behavior Computing, ABC 2019, IEEE, 2019-10-07)
    Data mining in education is a developing interdisciplinary research field also known as educational data mining (EDM). The goal is to understand students' learning process and identify the way by which they can learn to ...
  • Recognizing Hand-based Actions based on Hip-Joint centered Features using KINECT 
    Marouf, Ahmed Al; Sarker, Md. Ferdousur Rahman; Siddiquee, Shah Md. Tanvir (IEEE, 2018-07-19)
    Microsoft Kinect provides skeletal joints to extract different features which can be applied to identify different actions performed by subjects. As human moves, skeletal joints contribute to the movements and human actions ...
  • Recognizing Language and Emotional Tone from Music Lyrics Using IBM Watson Tone Analyzer 
    Marouf, Ahmed Al; Hossain, Rafayet; Sarker, Md. Rahmatul Kabir Rasel; Pandey, Bishwajeet; Siddiquee, Shah Md. Tanvir (Proceedings of 2019 3rd IEEE International Conference on Electrical, Computer and Communication Technologies, ICECCT 2023, IEEE, 2019-10-17)
    Music has a soothing impact on listener's mood and emotional states. Apart from the rhythm, sequence, instrumental effects on a song, lyrics could be considered as the most vital element. Lyricists' mood and affection ...

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