#Ridge-regression
Showing 8 of 8 repositories tagged #ridge-regression, ranked by stars
๐ฉ๐ปโโ๏ธCovid-19 estimation and forecast using statistical model; ๆฐๅๅ ็ถ็ ๆฏ่บ็็ป่ฎกๆจกๅ้ขๆต (Jan 2020)
Predicting Amsterdam house / real estate prices using Ordinary Least Squares-, XGBoost-, KNN-, Lasso-, Ridge-, Polynomial-, Random Forest-, and Neural Network MLP Regression (via scikit-learn)
A simple machine learning framework written in Swift ๐ค
Built house price prediction model using linear regression and k nearest neighbors and used machine learning techniques like ridge, lasso, and gradient descent for optimization in Python
By-hand code for models and algorithms. An update to the 'Miscellaneous-R-Code' repo.
Repository containing introduction to the main methods and models used in machine learning problems of regression, classification and clustering.
Demo from Data Community Bydgoszcz i Toruล, 27.02.2019
Understand the relationships between various features in relation with the sale price of a house using exploratory data analysis and statistical analysis. Applied ML algorithms such as Multiple Linear Regression, Ridge Regression and Lasso Regression in combination with cross validation. Performed parameter tuning, compared the test scores and suggested a best model to predict the final sale price of a house. Seaborn is used to plot graphs and scikit learn package is used for statistical analysis.