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.

Relevant Projects

Sequence Classification with LSTM RNN in Python with Keras
In this project, we are going to work on Sequence to Sequence Prediction using IMDB Movie Review Dataset​ using Keras in Python.

Data Science Project-TalkingData AdTracking Fraud Detection
Machine Learning Project in R-Detect fraudulent click traffic for mobile app ads using R data science programming language.

German Credit Dataset Analysis to Classify Loan Applications
In this data science project, you will work with German credit dataset using classification techniques like Decision Tree, Neural Networks etc to classify loan applications using R.

Predict Credit Default | Give Me Some Credit Kaggle
In this data science project, you will predict borrowers chance of defaulting on credit loans by building a credit score prediction model.

Build an Image Classifier for Plant Species Identification
In this machine learning project, we will use binary leaf images and extracted features, including shape, margin, and texture to accurately identify plant species using different benchmark classification techniques.

Learn to prepare data for your next machine learning project
Text data requires special preparation before you can start using it for any machine learning project.In this ML project, you will learn about applying Machine Learning models to create classifiers and learn how to make sense of textual data.

Human Activity Recognition Using Multiclass Classification in Python
In this human activity recognition project, we use multiclass classification machine learning techniques to analyse fitness dataset from a smartphone tracker.

Data Science Project in Python on BigMart Sales Prediction
The goal of this data science project is to build a predictive model and find out the sales of each product at a given Big Mart store.

Time Series Forecasting with LSTM Neural Network Python
Deep Learning Project- Learn to apply deep learning paradigm to forecast univariate time series data.

Demand prediction of driver availability using multistep time series analysis
In this supervised learning machine learning project, you will predict the availability of a driver in a specific area by using multi step time series analysis.