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Jan 26, 2020 - Jupyter Notebook
elastic-net-regression
Here are 32 public repositories matching this topic...
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Sep 30, 2020 - Jupyter Notebook
To know internal working of machine learning algorithms, I have implemented types of regression through scratch.
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Oct 12, 2020 - Jupyter Notebook
R code used for the analyses of the paper: Spatial conservation prioritisation in data-poor countries: a quantitative sensitivity analysis using different taxa
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Nov 9, 2020 - HTML
Explanations and Python implementations of Ordinary Least Squares regression, Ridge regression, Lasso regression (solved via Coordinate Descent), and Elastic Net regression (also solved via Coordinate Descent) applied to assess wine quality given numerous numerical features. Additional data analysis and visualization in Python is included.
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Jan 20, 2021 - Jupyter Notebook
Machine Learning Basics
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Feb 7, 2021 - Jupyter Notebook
I created multiple models to predict the discharge volume of a 100 year flood on rivers in NY state. The discharge of 100 year flood events is dependent upon watershed drainage area, and elevation among other variables.
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May 14, 2021 - R
This project compares the different machine learning models on Walmart Weekly Sales Data and predicts the weekly sales for the test data.
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May 25, 2021 - Jupyter Notebook
Algorithmes d’apprentissage et modèles statistiques: Un exemple de régression logistique régularisée et de validation croisée pour prédire le décrochage scolaire
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Jun 11, 2021 - Jupyter Notebook
My role in this group project was to perform regression analysis on quarterly financial data to predict a company's market capitalization. I used R to develop ordinary least squares (OLS), stepwise, ridge, lasso, relaxed lasso, and elastic net regression models. I first used stepwise and OLS regression to develop a model and examine its residual…
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Jun 29, 2021
Various Regression models including linear, polynomial, ridge, lasso and elastic net were experimented with to find which model best predicted health insurance costs. The models were evaluated using cross-validation, from which the best models were optimized using randomized search. The best model was then evaluated on the test data.
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Aug 18, 2021 - Jupyter Notebook
The project encompasses the statistical analysis of a high-dimensional data using different classification, feature selection, clustering and dimension reduction techniques.
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Nov 1, 2021 - Python
Data Models in R for Multiple Linear Regression and three models (Ridge, Lasso, and Elastic-Net), to predict Medicare claim costs of Type 2 diabetes patients with other diagnoses. We used Data from Entrepreneur’s Medicare Claims Synthetic Public Use Files (DE-SynPUFs) for our analysis.
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Dec 10, 2021
Logistic Regression technique in machine learning both theory and code in Python. Includes topics from Assumptions, Multi Class Classifications, Regularization (l1 and l2), Weight of Evidence and Information Value
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Dec 22, 2021 - Jupyter Notebook
Ridge, elastic net, and logistic regressions implemented without using any statistical or machine learning library. All steps are done by hand, using matrix operations as much as possible.
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Dec 22, 2021 - Jupyter Notebook
Machine learning (regression) exercise on prediction of house pricing in Melbourne with post-model analysis and recommendations for maximizing home value.
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Jan 18, 2022 - Jupyter Notebook
Lasso + Bootstrap methods for predictive modeling
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Jul 19, 2022 - R
Regression on BOSTON dataset from sklearn
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Oct 15, 2022 - Jupyter Notebook
A demonstration of the basic Machine Learning Algorithms
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Nov 13, 2022 - Jupyter Notebook
Regression analysis
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Jan 27, 2023 - Jupyter Notebook
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