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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
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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