Explain what is kernel density estimation with example?

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

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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