Solutions for practical projects of "Machine Learning" subject in UEA

Undirected graphical models are compact representations of joint probability distributions over random variables. To solve inference tasks of interest, graphical models of arbitrary topology can be trained using empirical risk minimization. However, to solve inference tasks that were not seen during training, these models (EGMs) often need to be…

The goal is to predict how likely individuals are to receive their H1N1 and seasonal flu vaccines. Specifically, you'll be predicting two probabilities: one for h1n1_vaccine and one for seasonal_vaccine. Each row in the dataset represents one person who responded to the National 2009 H1N1 Flu Survey. For details please visit the link: https://ww…

Ensemble Methods -- Stacking using Python

App made with pycaret and streamlit

Visual-analytical tools to evaluate and compare the outputs of large numbers of binary classifiers.

A collection of python notebooks that are implementing/using a plethora of machine learning methods.

Time Series

By leveraging ensemble learning, this program can be used to analyze the Linkage Disequilibrium between SNPs in each Indonesian rice chromosomes. Developed using Python 3.9.12.

In this paper, we developed a machine learning model ensemble approach consisting of a support vector machine (SVM), random forest (RF), Multilayer Perceptron (MLP), and Majority-VotingEnsemble classifiers.

Files for Machine Learning and Deep Learning with Different Models. Do Check!

Efficient Bayesian high-dimensional classification via random projection with application to gene expression data

Exploring a collection of Jupyter notebooks showcasing a variety of Natural Language Processing (NLP) projects.

Jupyter notebook for IoT threat detection using ensemble machine learning. Features data preprocessing, model training (Logistic Regression, Decision Trees, Neural Networks, etc.), and ensemble techniques for enhanced accuracy.

A customer churn classification project, build the model to predict whether a customer will leave the bank (churn) or not.

Popularity Prediction in Spotify Dataset using Ensemble Learning

Scientific Initiation Reports in Computer Engineering and Astronomy

This project focuses on leveraging AutoGluon's 'Tabular Prediction' to create accurate AutoML-based baseline models to predict the bike sharing demand using the Kaggle Bike Sharing demand dataset.

This project focuses on predicting the Myers-Briggs Personality Type Indicator (MBTI) using various machine learning techniques. MBTI is a type indicator that categorizes individuals into one of 16 personality types based on their preferences in four dimensions: Introversion/Extraversion, Sensing/Intuition, Thinking/Feeling, and Judging/Perceiving.

The Method for Optimal Classification by Aggregation (MOCA) package for the Python programming language.