Case study on regularisation methods for statistics and machine learning
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Updated
Jun 3, 2019 - R
Case study on regularisation methods for statistics and machine learning
Developed student performance predicting model, showing strong understanding of predictive modeling techniques.
Linear regression, ridge, lasso
Hello! All codes belong to me. I created those codes for my Machine Learning Lab Class. Enjoy it!
I compare the accuracy of health cost prediction of four regression models: Linear, Lasso, Ridge, and Elastic Net Regression.
In this project, we use differents methods to transform our dataset (usually dimension modification) before making prediction thanks to machine learning and regressions.
This repository shows some coding in R my colleagues and I made for our Machine Learning course for the Diploma of Specialization in Data Science for Social Sciences and Public Management - PUCP
Use of different regression models to predict bike demand.
Diamonds Price prediction using Polars and Ski-learn
This is the python implementation of linear regressions. The repo consists of ordinary linear regression, lasso linear regression, ridge linear regression
Regression Analysis to predict car selling price with given datasets. Used libraries: Pandas, Matplotlib, Seaborn, Scikitlearn
Analysis of Influencing Factors Leading to Suicidal Actions via Linear Regression and Regularization Methods
Group project to analyze the causes of inequality in Brazil
Superstore clusters prediction with Lasso and Ridge
Exploratory data analysis and supervised learning analysis on the Ames Housing Prices dataset.
Predicting house prices
Repository for my Master's thesis comparing volatility models.
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