Gene classification and pattern analysis using data mining and machine learning techniques

Gene classification and pattern analysis using data mining and machine learning techniques

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021.

Bibliografske podrobnosti
Main Authors:	Ramisa, Aiman Jabeen, Hossain, Ananna, Islam, Sk Md Injamul, Swadesh, Ponuel Mollah, Islam, Md. Toushif
Drugi avtorji:	Parvez, Mohammad Zavid
Format:	Thesis
Jezik:	English
Izdano:	Brac University 2021
Teme:	Classification Feature Selection Accuracy Pattern Extraction Gene Classification Application of Machine Learning Machine Learning Data mining
Online dostop:	http://hdl.handle.net/10361/15185

Podobne knjige/članki

A framework for sentiment analysis: a data-driven approach
od: Islam, Md. Jahedul, et al.
Izdano: (2021)

Music genre classification with convolutional neural network
od: Chowdhury, Masud, et al.
Izdano: (2022)

Text classification using machine learning algorithms
od: Hasnat, Fahim, et al.
Izdano: (2018)

Heartbeat sound feature extraction and classification
od: Bibrity, Fariha Chowdhury, et al.
Izdano: (2020)

Machine learning based data processing and latency reduction in the internet of things for agriculture
od: Rahman, Sajeed Ur, et al.
Izdano: (2019)

Child Safe Browser Extension: A Browser Extension to Detect Adultery and Violent Content to Make Safer Web for Children
od: Alhossen, Md., et al.
Izdano: (2021)

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

Deep convolutional GAN-based data augmentation for medical image classification
od: Datta, Joy, et al.
Izdano: (2022)

Classification of Bangladeshi soil texture using convolutional neural network
od: Raj, Hafiz Mohiuddin, et al.
Izdano: (2023)

Classification of music based on correlation between mood, linguistic and audio features
od: Sobhan, Md. Mashrur Bari
Izdano: (2018)

Skin cancer detection and classification using multiple optimized deep convolutional neural network
od: Sakir, Adnan, et al.
Izdano: (2023)

Comparison of different CNN architectures for brain tumor detection using fMRI
od: Mashiat, Afsara, et al.
Izdano: (2021)

Pattern recognition and machine learning /
od: Bishop, Christopher M.
Izdano: (2006)

An efficient deep learning approach to detect skin cancer using image data
od: Chowdhury, Yaser Al Rahman, et al.
Izdano: (2023)

Detection and prediction of epileptic seizure using different machine learning classifiers
od: Crystal, Afnan Ahmed, et al.
Izdano: (2023)

Classification of retinal diseases from OCT images using deep learning models
od: Mokarrom, Md Saif, et al.
Izdano: (2024)

Bang-lish sentiment classification using deep learning
od: Saleheen, Abrar, et al.
Izdano: (2023)

Recognition of Bangladeshi sign language from 2D videos using openpose and LSTM based RNN
od: Dewanjee, Tanmoy, et al.
Izdano: (2021)

Predicting crime using deep learning
od: Shihab, Muhammad Nafees, et al.
Izdano: (2024)

What is relevant in a text document a machine learning based approach
od: Mahmud, Abdullah Al, et al.
Izdano: (2021)

An efficient deep learning approach to detect skin Cancer
od: Islam, Ashfaqul, et al.
Izdano: (2022)

Deep learning-based waste classification system for efficient waste management
od: Nakib, Abdullah Al, et al.
Izdano: (2022)

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

Verifying online signatures through an iterative device independent model
od: Tahsin, Samiha, et al.
Izdano: (2024)

Emotion recognition from facial expression of autism spectrum disordered children using image processing and machine learning algorithms
od: Tasnim, Nishat, et al.
Izdano: (2019)

Classifying insect pests from image data using deep learning
od: Mohsin, Md. Raiyan Bin, et al.
Izdano: (2022)

Fake profile detection in social media using image processing and machine learning
od: Sen, Shuva, et al.
Izdano: (2021)

Prostate cancer detection using deep learning neural network with transfer learning approach
od: Badhon, Ariful Islam Mahmud, et al.
Izdano: (2022)

Classification of different magnetic structures from image data using deep neural networks
od: Ibn Hasib, Fahad, et al.
Izdano: (2023)

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

Classification of peripheral blood cell images using deep learning
od: Aadi, Oyshik Ahmed, et al.
Izdano: (2024)

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

A domain and noise adversarial bird tune classification pipeline using deep neural network
od: Riya, Aparna Sarker, et al.
Izdano: (2023)

An implementation and analysis of deep learning models for the detection of wheat diseases
od: Zubair, Ahmad, et al.
Izdano: (2024)

Gene expression analysis using machine learning
od: Mostafa, Naﬁs
Izdano: (2021)

A novel lightweight CNN approach for Bangladeshi sign language gesture recognition
od: Rahman, Aryan, et al.
Izdano: (2023)

Genre classification of movies using their synopsis
od: Rahman, Ramiz Ihteshamur, et al.
Izdano: (2018)

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

Automatic waste classification using deep learning and computer vision techniques
od: Akash, MD., et al.
Izdano: (2023)

Detection of handwritten text using convolutional neural network
od: Jasim, Rabib Bin, et al.
Izdano: (2024)