Machine Learning model which uses closed-form solution of Locally Weighted Regression (LOWESS) Algorithm to predict the Quality of Air
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Updated
Aug 23, 2019 - Python
Machine Learning model which uses closed-form solution of Locally Weighted Regression (LOWESS) Algorithm to predict the Quality of Air
Robust locally weighted multiple regression in Python
Predicting quasar spectra using functional regression(Nadaraya-Watson model)
Contains submissions of the Soft Computing Elective Course at IIITA.
VTU Machine Learning lab programs in Python (2015 SCHEME)
Tips given at restaurants modelled using the memory intensive Locally-Weighted-Regression.
This linear Regression is specificly for polynomial regression with one feature. It contains Batch gradient descent, Stochastic gradient descent, Close Form and Locally weighted linear regression.
Locally Weighted Regression
Programming assignment code of Computational Statistics taught at IIT Kharagpur by Prof. Swanand Ravindra Khare
An Open-Source Python framework for Locally Weighted Regression and Classification, built on PyTorch and Scikit-Learn
This project leverages Polynomial Regression to predict building energy consumption, focusing on both heating and cooling loads. It features in-depth exploratory data analysis, and robust model evaluation to optimize prediction accuracy for energy-efficient building design.
(VTU) aritficial Intelligence and machine learning practical programs and algorithms
Machine Learning Assignments of the course COL774 taken by Parag Singla, at IIT Delhi.
Regression models on Boston Houses dataset
numpy implementation of mere and locally-weighted logistic regression for binary classification problem.
ML using NumPy and Pandas
A few generalized linear models and one Gaussian discriminant analysis
This repository contains implementations of advanced regression methods, including ordinary least squares, Poisson regression, and locally weighted regression. It also explores bias-variance decomposition for regularized mean estimators. The analysis is conducted on the Capital Bikesharing dataset using Python.
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