Predict appliance energy consumption (Wh) from indoor sensor readings and outdoor weather data. Estimate the number of occupants in a room (0–3 people) from multi-modal IoT sensor streams. Implements ...

Abstract: Logistic regression is widely used for binary classification; however, its performance in real-world applications is often hindered by multicollinearity, high-dimensional feature spaces, and ...

Logistic regression is a statistical method used to model binary outcome variables, such as whether a patient recovers or not, using a set of predictors. There are many competing methods for ...

Artificial intelligence is rapidly changing the job market, automating jobs across industries. Therefore, in such a scenario, upskilling oneself in industry-relevant AI skills becomes even more ...

Automatic detection of cognitive distortions from short written text could support large-scale mental-health screening and digital cognitive-behavioural therapy (CBT). Many recent approaches rely on ...

Abstract: Logistic regression for functional data is a statistical technique for modeling the relationship between functional predictor variables and a binary or multiclass outcome variable. The model ...

The rapid uptake of supervised machine learning (ML) in clinical prediction modelling, particularly for binary outcomes based on tabular data, has sparked debate about its comparative advantage over ...

There was an error while loading. Please reload this page. This project applies Logistic Regression to predict whether a passenger aboard the Titanic survived. It ...

Department of Mathematics, Statistics and Actuarial Science, Faculty of Health, Natural Resources and Applied Sciences, Namibia University of Science and Technology, Windhoek, Namibia. Food insecurity ...