A machine learning approach to predict young voter enthusiasm based on non-political factors

A machine learning approach to predict young voter enthusiasm based on non-political factors

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2020.

Bibliographische Detailangaben
Hauptverfasser:	Rahman, Md. Nowroz Junaed, Pantho, Md. Humaun Kabir, Fuad, Nafis
Weitere Verfasser:	Majumdar, Mahbubul Alam
Format:	Abschlussarbeit
Sprache:	en_US
Veröffentlicht:	Brac University 2021
Schlagworte:	Machine Learning Voting Young Voter Turnout Random Forest Support Vector Machine XGBoost Naive Bayes Non-political
Online Zugang:	http://hdl.handle.net/10361/14463

Ähnliche Einträge

Intrusion of Malware (DDoS) detection in IoT devices using Machine Learning on Cyberspace
von: Al Amin, Istiak, et al.
Veröffentlicht: (2022)

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

Parking data analysis
von: Ahamed, Kasfi, et al.
Veröffentlicht: (2023)

Sentimental analysis of food review contents to improve food culture and the quality of virtual content using natural language processing and machine learning
von: Sarkar, Ripa, et al.
Veröffentlicht: (2024)

Assistive Guideline of Categorization for Competitive Programming Problems
von: Dhrubo, Najmus Sakib, et al.
Veröffentlicht: (2021)

A hybrid rumor detection model derived from a comparative study of supervised approaches
von: Aothoi, Mehzabin Sadat, et al.
Veröffentlicht: (2023)

Best feature selection and data visualization for breast cancer prediction
von: Hemel, Tanjim Ahmed, et al.
Veröffentlicht: (2020)

Prediction of earthquakes: a step towards predicting the unpredictable
von: Chowdhury, Maheen, et al.
Veröffentlicht: (2023)

Diagnosis of cervical cancer using effective hybrid model in Bangladesh
von: Saad-Ul-Kabir, Syed, et al.
Veröffentlicht: (2021)

Performance analysis of machine learning algorithms for Malware classification
von: Bushra, Raisa Hasan, et al.
Veröffentlicht: (2023)

Fighting depression: psychological approaches among Bangladeshi university students
von: Sen, Sanjib Kumar, et al.
Veröffentlicht: (2022)

SCAMM: detection and prevention of SQL injection attacks using a machine learning approach
von: Alam, Auninda, et al.
Veröffentlicht: (2021)

Cardiovascular disease prediction model using Machine Learning Algorithm
von: Arefin Mirdha, MD Shamsul
Veröffentlicht: (2023)

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

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

Rating detection by reviews using ML and NLP towards mobile phone recommendation
von: Sarker, Md Wafi, et al.
Veröffentlicht: (2023)

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

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

Estimating flood susceptibility of Bangladesh in the future year using machine learning
von: Alim, Sakib Bin, et al.
Veröffentlicht: (2021)

Predicting subject area interest of a student using naive bayes
von: Hossain, Shakib
Veröffentlicht: (2016)

Machine learning-based approach on predicting online shopping addiction using EEG signals
von: Nawer, Nafisa, et al.
Veröffentlicht: (2023)

Multimodal fake news detection using text and image
von: Biswas, Trisha, et al.
Veröffentlicht: (2024)

Automatic classified myocardial infarction detection using machine learning and forewarning system with location of the patient using GSM module
von: Shrestha, Soptorsi Paul, et al.
Veröffentlicht: (2021)

Recognizing sentimental emotions in text by using Machine Learning
von: Bushra, Tabassum Khan, et al.
Veröffentlicht: (2023)

Stock market prediction using ensemble learning
von: Rabbani, Rakin Bin, et al.
Veröffentlicht: (2021)

Heart disease prediction using techniques of classification in machine learning
von: Afrose, Sadia, et al.
Veröffentlicht: (2021)

Comparative analysis and implementation of credit risk prediction through distinct machine learning models
von: Turjo, Aquib Abtahi, et al.
Veröffentlicht: (2021)

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

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

A feature selection approach to determine obesity using machine learning method
von: Antor, Shahidul Alam, et al.
Veröffentlicht: (2021)

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

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

Machine learning based analysis and prediction of crop yield and prices of Aman, Aus and Boro rice
von: Bhattacharjee, Ruposri, et al.
Veröffentlicht: (2024)

Heart disease prediction system
von: Amit, Tayab Al Azad, et al.
Veröffentlicht: (2022)

An effective machine learning approach for sentiment analysis of restaurant reviews
von: Karim, Rabita
Veröffentlicht: (2018)

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

Unveiling underlying patterns, drivers and anomalies in cryptocurrency price dynamics through feature fusion of financial indicators and sentiment fluctuations
von: Rabbi, Md. Nafis
Veröffentlicht: (2024)

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

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

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