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使用python完成回归分析，再绘制解释变量和响应变量的散点图

Nov 17, 2024

使用python完成回归分析，再绘制解释变量和响应变量的散点图

python

Explanation

This code performs regression analysis using Python and visualizes the relationship between the independent variable (X) and the dependent variable (y) through a scatter plot and a regression line.

Step-by-step Instruction

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Generate sample data: Create random data for the independent variable and generate the dependent variable with some noise

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Create a DataFrame: Combine the independent and dependent variables into a pandas DataFrame for easier handling

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Initialize and fit the model: Create a LinearRegression model and fit it to the data

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Predict values: Use the fitted model to predict the dependent variable values based on the independent variable

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Plot the results: Create a scatter plot of the original data and overlay the regression line

Time Complexity

The time complexity is O(n) for fitting the model, where n is the number of data points.

Space Complexity

The space complexity is O(n) for storing the data points and the model parameters.