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Model verification, validation, and error analysis
Decompose a signal/timeseries into structure and noise or seasonal and residual components
A MATLAB function for robust non-linear least squares
Detection of Object-Based Forgery in Advanced Video
Surrogate residuals for cumulative link and general regression models in R
Clean up Windows software uninstall residual files. 清理Windows软件卸载残留。
Python script to plot residual data in OpenFOAM case folders written out by Eddy3D (www.eddy3d.com), an airflow and microclimate simulations plugin for Rhino and Grasshopper.
Predictive Analysis Course's notes for Computer Science B.S. at Ca' Foscari University of Venice
使用AIC准则进行参数选择,之后采用ARIMA模型进行时间序列预测,最后给出残差图。The AIC criterion is used to select the parameters, and then ARIMA model is used to predict the time series. Finally, the residual diagram is given.
Detailed implementation of various regression analysis models and concepts on real dataset.
University group project concerning the sensorless estimation of the contact forces between a needle mounted on the end-effector of a robot manipulator and a penetrated tissue, and subsequent prediction of layer ruptures using Recursive Least Squares algorithm.
Used linear regression model to train and test the data, evaluated the model performance by calculating the residual sum of squares and the explained variance score (R^2).
Using the admission dataset. Reply the following questions. Using R. 1) Test if there is any relation (linear or exponential) between the following pair of variables: a) SSC Marks Obtained and NU_BS_Test Marks b) SSC Marks Obtained and NU_BS_Test Marks c) SSC Marks Obtained and HSSC Marks Obtained 2) Plot the residual plots for the parts in Question No 1 3) Calculate r2 the each part of question no 1 and confirm it by calculating the same by using the residuals.
Prediction of Salary of individuals based on years of experience
Numerical Methods: "Life Expectancy & Linear Regression" Group Project - 2nd Semester 2021 - Computer Science, UBA
Predicting Delivery Time Using Sorting Time
Simple Linear Regression
Compute a moving mean squared error (MSE) incrementally.
Compute a moving root mean squared error (RMSE) incrementally.
Compute a moving residual sum of squares (RSS) incrementally.
Compute the mean squared error (MSE) incrementally.
Compute the root mean squared error (RMSE) incrementally.
Compute the residual sum of squares (RSS) incrementally.
Detailed implementation of various time series analysis models and concepts on real datasets.
analysis of contingency tables and their residuals, with a bootstrap correction for multiple testing
Analyze trends and forecast daily revenues.
Linear regression is also a type of machine-learning algorithm more specifically a supervised machine-learning algorithm that learns from the labeled datasets and maps the data points to the most optimized linear functions.
This repository contains code for a bike rental prediction models including Random Forest, XGBoost, GradientBoosting, and Lasso Regression.
Prediction-model-for-predicting-Price-of-Cars
This repository generates diagnostic plots of residuals using the performance and see packages
Linear Multilinear and Logistic Regression in Machine Learning
This project uses time series forecasting to predict future milk production. The data used in this project is monthly milk production data from January 1962 to December 1975. The ARIMA (autoregressive integrated moving average) model is used to forecast the milk production. The model is evaluated using various metric.