plot logistic regression curve in python

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In this tutorial, we will explore how to plot a logistic regression curve using Python. Logistic regression is a popular method for binary classification problems, and visualizing the logistic regression curve can help us understand the decision boundary of the model. We will use the scikit-learn library for logistic regression and matplotlib for visualization.
Make sure you have the necessary libraries installed. You can install them using the following commands:
Let's generate some sample data for demonstration purposes. In a real-world scenario, you would replace this with your actual dataset.
Here, we generate random values for X and create a binary target variable y based on a threshold value of 5.
To visualize the logistic regression curve, we can create a scatter plot of the data points and overlay the logistic regression curve.
This code snippet generates a scatter plot of the data points and overlays the logistic regression curve. The predict_proba method is used to obtain the predicted probabilities, and the curve is plotted using matplotlib.
By following this tutorial, you have learned how to plot a logistic regression curve in Python using the scikit-learn and matplotlib libraries. Visualizing the logistic regression curve is helpful in understanding the decision boundary of the model in binary classification problems.
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