There are 2 repositories under elastic-net topic.
Generalized Linear Regressions Models (penalized regressions, robust regressions, ...)
次元期权应征面试题范例。
Analyzes weightlifting videos for correct posture using pose estimation with OpenCV
Slides and notebooks for my tutorial at PyData London 2018
A chronological age predictor based on DNA methylation
Predicting Baseball Statistics: Classification and Regression Applications in Python Using scikit-learn
Feature selection method based on repeated elastic net.
Experiments in ML with tidymodels
Training ensemble machine learning classifiers, with flexible templates for repeated cross-validation and parameter tuning
Elastic-net VARMA: hyperparameter optimisation, estimation and forecasting
転職サイトから、年収の条件を明らかにし、良さげな条件とは何かを明らかにします
Integrative Survival Models
A fast version of elastic net r-package based on RcppArmadillo
SQL Build Manager is an all-in-one database management tool to easily update your fleet SQL Server databases - from one to tens of thousands.
It is From Analytics Vidhya Hackathons, Sponsored by Club Mahindra. It is based on Regression Problem, Where Accuracy matters the most, It is measured by RMSE Score. Different Techniques such as Stacking, Ensembling, Boosting and Scientific Operations such box-cox Operations to reduce skewness of the data.
A multi-tissue transcriptional age calculator
LASSOPACK: Stata module for lasso, square-root lasso, elastic net, ridge, adaptive lasso estimation and cross-validation
In this project, I am applying your frequentist inference and regression modelling skills to different datasets. I applied several machine learning algorithms and try to answer research questions of related problems and also perform data visualization to justify my results.
Demo of Elastic Search using C#
A Python package which implements the Elastic Net using the (accelerated) proximal gradient method.
This is the website repository for the Stata packages lassopack & pdslasso. Please visit:
Machine learning demonstration of the Gradient Boosting algorithm and it's effectiveness on a regression dataset of house prices.
Predicting house price