There are 1 repository under generalized-additive-models topic.
Collection of must read papers for Data Science, or Machine Learning / Deep Learning Engineer
ggplot-based graphics and useful functions for GAMs fitted using the mgcv package
{mvgam} R 📦 to fit Dynamic Bayesian Generalized Additive Models for time series analysis and forecasting
A document introducing generalized additive models.📈
This is a Statistical Learning application which will consist of various Machine Learning algorithms and their implementation in R done by me and their in depth interpretation.Documents and reports related to the below mentioned techniques can be found on my Rpubs profile.
GAMI-Net: Generalized Additive Models with Structured Interactions
A workshop on using generalized additive models and the mgcv package.
ggplot-based graphics and useful functions for GAMs fitted using the mgcv package
Ecological forecasting using Dynamic Generalized Additive Models with R 📦's {mvgam} and {brms}
Fit, evaluate, and visualise generalised additive models (GAMs) in native Julia
Workshop 8 - Generalized additive models (GAMs)
An introduction to GAM(M)s
A function that takes as input a cropped text line image, and outputs the dewarped image.
Paper on identifying patterns in economic development using statistical learning
This repository contains the script and figures of the conference paper selected for presentation at the Latin American Conference of Computationa Intelligence 2018. The abstract of the paper is as follows: Crime is an important social and economic problem of South Africa. Though certain categories of crimes are of serious proportions, yet on aggregate the overall crime situation in the country has considerably improved in the last decade or so. A number of previous studies across other countries have shown a positive or negative relationship between crime and economic growth. On a microeconomic/provincial scale, this paper studies the relationship between various categories of crimes and economic growth using the non-linear modeling technique of Generalized Additive Models. Such a modeling approach helps in understanding how various categories of crimes complexly affect GDP.
GAM workshop for NHS-R Community Conference 2023
The dataset used for the "Non-Contact Blood Pressure Estimation using infrared motion magnified facial video" publication. The code developed is to fit the data to the reference Blood Pressure values.
The dataset used for the "A non-contact SpO2 estimation using video magnification and infrared data" publication
Rcpp package implementing automatic smoothing for multiple generalized additive models.
Overview of statistical learning methods for classification
National Centre for Statistical Ecology seminar, Feb 9th, 2022
Explainable Recommendation Systems
Using generalized additive models to analyze COVID-19 US county level mortality data
Predicting Elections Using GAMs and Post-Stratification
Analysis of data from the Framingham Heart Study using generalized linear models.
Example machine learning implementation to predict the residual bending moment capacity of corroded reinforced concrete beams tested under monotonic three or four-point bending. Data is collected from 54 experimental programs available in the literature.
A project for modeling atmospheric data to try to predict temperature values using a linear model and a generalized additive model