Using the data from Step 4, create a second StatsModels linear regression model using one numeric feature and one one-hot encoded categorical feature. 6. Evaluate and Interpret Multiple Linear Regression Model Results Explain the performance of the new model in comparison with the baseline, and int...
The choice oflogistic regression(LR) is supported by its simplicity and common use for text classification [60]. Depending on the features, LR can obtain good results in online hate detection with low model complexity [76]. As such, including LR when comparing different models seems rational. ...
Multiple Linear Regression - Cumulative Lab Introduction In this cumulative lab you'll perform an end-to-end analysis of a dataset using multiple linear regression. Objectives You will be able to: Prepare data for regression analysis using pandas Build multiple linear regression models using StatsModel...
Explore and run machine learning code with Kaggle Notebooks | Using data from No attached data sources
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Explore and run machine learning code with Kaggle Notebooks | Using data from Startup - Multiple Linear Regression
Explore and run machine learning code with Kaggle Notebooks | Using data from Student Performance (Multiple Linear Regression)
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