Topic: "r-squared"
LastAncientOne/GDP_Project
GDP Forcasting
Size: 1.49 MB - Last synced at: 2 months ago - Pushed at: over 3 years ago - Stars: 5 - Forks: 1
YenLinWu/Daily_Work_of_Data_Science
資料科學的日常研究議題
Language: Jupyter Notebook - Size: 19.1 MB - Last synced at: 19 days ago - Pushed at: 19 days ago - Stars: 3 - Forks: 1
nikolas-virionis/linear-regression-model
An npm package to make it easier to deal with a handful of values, and try to model them in one of the most used mathematical models, with an R/Numpy-like accuracy algorithm
Language: JavaScript - Size: 52.7 KB - Last synced at: 3 days ago - Pushed at: almost 3 years ago - Stars: 3 - Forks: 1
e-paj/Machine-Learning-Projects-in-Python
This repository contains all the Machine Learning projects I did using different Machine Learning methods. Python being the main software used.
Language: Jupyter Notebook - Size: 7.88 MB - Last synced at: about 1 year ago - Pushed at: almost 3 years ago - Stars: 2 - Forks: 1
hamza-mughees/Line-of-Best-Fit
This project calculates the equation of the line of best fit of a given correlation
Language: Python - Size: 460 KB - Last synced at: almost 2 years ago - Pushed at: almost 5 years ago - Stars: 2 - Forks: 0
stdlib-js/stats-incr-pcorr2
Compute a squared sample Pearson product-moment correlation coefficient.
Language: JavaScript - Size: 918 KB - Last synced at: 13 days ago - Pushed at: 19 days ago - Stars: 1 - Forks: 0
stdlib-js/stats-incr-mpcorr2
Compute a moving squared sample Pearson product-moment correlation coefficient incrementally.
Language: JavaScript - Size: 990 KB - Last synced at: 13 days ago - Pushed at: 5 months ago - Stars: 1 - Forks: 0
SAI-SRINIVASA-SUBRAMANYAM/machine_practices_problems
Language: Jupyter Notebook - Size: 37.1 KB - Last synced at: 6 months ago - Pushed at: over 2 years ago - Stars: 1 - Forks: 1
hardikasnani/diamond-price-and-carat-prediction
I leveraged an algorithmic approach to predict the price and carat of the diamond using Machine Learning. Various regression models have been trained and their performance has been evaluated using the R Squared Score followed by tuning of the hyperparameters of top models. I have also carried out a trade-off based on the R Squared Score and the Run-Time to take a situational decision to select the best model.
Language: Jupyter Notebook - Size: 694 KB - Last synced at: almost 2 years ago - Pushed at: almost 3 years ago - Stars: 1 - Forks: 2
Wb-az/MLib-PySpark-SoundLevel-Prediction
Creates a ML Pipeline leveraging PySpark SQL and PySpark MLib to predict sound level
Language: Jupyter Notebook - Size: 972 KB - Last synced at: about 2 months ago - Pushed at: 3 months ago - Stars: 0 - Forks: 0
pngo1997/Learning-to-Rank-Algorithm
Builds a ranking model to predict the relevance score for query-product pairs in HomeDepot’s product search.
Language: Jupyter Notebook - Size: 19.7 MB - Last synced at: about 2 months ago - Pushed at: 3 months ago - Stars: 0 - Forks: 0
IotchulindraRai/MILK_sales_Production
Collect and preprocess historical sales data of Sujal Dairy Pvt. Ltd. to understand trends. Implement regression models like linear regression, decision trees, or advanced models like LSTM, based on data complexity. Validate model accuracy using metrics such as RMSE, MAE, and R-squared.
Language: Jupyter Notebook - Size: 316 KB - Last synced at: 21 days ago - Pushed at: 3 months ago - Stars: 0 - Forks: 0
OscarTMa/Regression-Project
Regression is a fundamental supervised machine learning technique used to predict continuous numerical outcomes based on input features.
Language: Jupyter Notebook - Size: 307 KB - Last synced at: 24 days ago - Pushed at: 5 months ago - Stars: 0 - Forks: 0
RichaSavant/Stock-Market-Analysis-A-Two-Stage-Comparative-Stacking-Approach-using-Pyspark-Jan_2024
This project aims to enhance the accuracy and efficiency of stock market predictions by employing a sophisticated machine learning methodology. This project leverages the power of PySpark, a robust framework for distributed data processing, to handle large datasets and perform complex computations.
Size: 23.8 MB - Last synced at: about 2 months ago - Pushed at: 9 months ago - Stars: 0 - Forks: 0
Saxsori/ft_linear_regression
An introduction to machine learning
Language: Python - Size: 146 KB - Last synced at: 10 months ago - Pushed at: 10 months ago - Stars: 0 - Forks: 0
aleniart/multiple_linear_regression_customers
Multiple linear regression model based on eCommerce customers data in Python language.
Language: Jupyter Notebook - Size: 3.6 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0
EmamulHossen/Feature-Transformation-Assignment-6.3-
Feature transformation is a technique in machine learning that is used to modify the original features of a dataset in order to improve the performance of machine learning algorithms.
Language: Jupyter Notebook - Size: 61.5 KB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0
anilesh-prajapati/Probability-and-Statistics-for-Machine-Learning
Probability and Statistics for Machine Learning
Language: Jupyter Notebook - Size: 1.03 MB - Last synced at: about 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0
NavindaFernando/Heart-Risk-Prediction-Model
Heart Risk Level Predicting Regression Model :broken_heart:
Language: Jupyter Notebook - Size: 45.9 KB - Last synced at: 2 months ago - Pushed at: almost 2 years ago - Stars: 0 - Forks: 0
rudycav/World-Happiness-Scores
Functional specification to calculate per country's happiness score
Language: R - Size: 419 KB - Last synced at: over 1 year ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 0
saboye/predicting-sales-performance
project to predict smartphone sales based on the marketing budget spent on advertising using three platforms involves collecting data on marketing spending and smartphone sales, and using statistical and machine learning techniques to build a model that can predict future smartphone sales based on changes in marketing budget.
Language: Jupyter Notebook - Size: 501 KB - Last synced at: over 1 year ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 0
ashishyadav24092000/Multiple-Linear-Regression
Performing multiple linear regression on a simple dataset.
Language: Jupyter Notebook - Size: 14.6 KB - Last synced at: over 1 year ago - Pushed at: almost 3 years ago - Stars: 0 - Forks: 0
EmmaSui/Business-Analytics-Predicting-Catalog-Demand
Using multiple linear regression model to predict customer demand in order to make business decision
Language: Jupyter Notebook - Size: 281 KB - Last synced at: almost 2 years ago - Pushed at: about 3 years ago - Stars: 0 - Forks: 0
jilek/MechaCar_Statistical_Analysis
Statistical analysis to predict the importance of various manufacturing parameters on fuel economy of a prototype car.
Language: HTML - Size: 492 KB - Last synced at: about 2 years ago - Pushed at: almost 4 years ago - Stars: 0 - Forks: 0
devosmitachatterjee2018/Linear_Statistical_Models
The project involves the multivariate regression analysis of a dataset.
Language: R - Size: 1.72 MB - Last synced at: almost 2 years ago - Pushed at: over 4 years ago - Stars: 0 - Forks: 0
