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Regression

A guide to Regression
Data Understanding Data Preparation Modelling & Evaluation To convert the categorical variables tonumbers, there are two ways. One-Hot-Encoding and category to number. In thisworkflow, the One-Hot_encoding was useddue to being as similar as the blogpostsource. However, the latter can be used aswell. This workflow includes the codes of the article of Complete Guide to Regressional Analysis Using Python byBrandon Morgan.https://towardsdatascience.com/complete-guide-to-regressional-analysis-using-python-bbe76b3e451fTo To understand the workflow, one can go through the above article and run each step separately. Before running the workflow, you need to prepare the anaconda (Python) environment. To this end, download thefolowing file and run the blow command in the anaconda environment.- environment file path:https://drive.google.com/file/d/1CSg9na5-UFUp42v9rFL0AzZgq518xtg0/view?usp=sharing- open anaconda or cmd on your machine, locate the path you coppied the environment.yml file, then run thiscommandconda env create --file environment.yml Loading datasetNode 8SplittingTrain/TestCalculating log of trgetHeatmapNode 16One-Hot EncodingRemoving original target CSV Reader Descriptive Stats Category To Number Partitioning Math Formula Python View Conda EnvironmentPropagation Python Script Column Filter Linear Regression Kernel Regression Overfitting SVM Compare Data Understanding Data Preparation Modelling & Evaluation To convert the categorical variables tonumbers, there are two ways. One-Hot-Encoding and category to number. In thisworkflow, the One-Hot_encoding was useddue to being as similar as the blogpostsource. However, the latter can be used aswell. This workflow includes the codes of the article of Complete Guide to Regressional Analysis Using Python byBrandon Morgan.https://towardsdatascience.com/complete-guide-to-regressional-analysis-using-python-bbe76b3e451fTo To understand the workflow, one can go through the above article and run each step separately. Before running the workflow, you need to prepare the anaconda (Python) environment. To this end, download thefolowing file and run the blow command in the anaconda environment.- environment file path:https://drive.google.com/file/d/1CSg9na5-UFUp42v9rFL0AzZgq518xtg0/view?usp=sharing- open anaconda or cmd on your machine, locate the path you coppied the environment.yml file, then run thiscommandconda env create --file environment.yml Loading datasetNode 8SplittingTrain/TestCalculating log of trgetHeatmapNode 16One-Hot EncodingRemoving original target CSV Reader Descriptive Stats Category To Number Partitioning Math Formula Python View Conda EnvironmentPropagation Python Script Column Filter Linear Regression Kernel Regression Overfitting SVM Compare

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Created by: Ehsan.Taati
Created at: 2021-12-10
On NodePit since: 2022-01-16
Last update: 2024-04-27
Created with KNIME version: v4.5.0
Tags: RegressionPythonMachine LearningSVMLinear RegressionKernel RegressionResidual analysisL2 Regularisation

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