Explain what is kernel density estimation with example?
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Explain what is kernel density estimation with example?

Explain what is kernel density estimation with example?

This recipe explains what is kernel density estimation with example

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Recipe Objective?

what is kernel density estimation? Explain with example

kernel density estimation this method is a way of estimating the probability density function of continuous random variables. The plot is used for visualizing the distribution of observation in a dataset, analogous to histogram. It represents the data using a continuous probability curve in one or more than one dimensions.

Step 1 - Import the necessary library

import seaborn as sns

Step 2 - load the dataset

iris_data = sns.load_dataset('iris') iris_data.head()

Step 3 - Plot the graph

sns.kdeplot(data=iris_data, x='sepal_length)

Here in the above figure: data - denotes the Sample data name that we have taken. x - denotes which variable to be plot on x-axis.

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