What are Asymmetric Kernels in the StatsModels library?

This recipe describes what are Asymmetric Kernals in the StatsModels library

Get access to Data Science projects View all Data Science projects
MACHINE LEARNING PROJECTS IN PYTHON DATA CLEANING PYTHON DATA MUNGING MACHINE LEARNING RECIPES PANDAS CHEATSHEET     ALL TAGS

Recipe Objective - What are Asymmetric Kernels in the StatsModels library?

Asymmetric kernels such as unit interval beta and positive random variable gamma avoid problems at the limits of supporting distribution. Statsmodels provides preliminary support for estimating density and cumulative distribution functions using the kernels of unit intervals, beta, or positive actual lines and all other kernels. Some kernels of positive real lines assume zero density at the zero boundary. With gamma kernels, positive or non-bonding densities at the zero limit are also possible. Currently there is no default setting and bandwidth selection is not supported. The user must provide bandwidth.

List of Classification Algorithms in Machine Learning  

For more related projects -

https://www.dezyre.com/projects/data-science-projects/deep-learning-projects
https://www.dezyre.com/projects/data-science-projects/neural-network-projects

The functions for calculating the kernel density and kernel CDF are:

pdf_kernel_asym(x, sample, bw, kernel_type)
Density estimate based on asymmetric kernel.

cdf_kernel_asym(x, sample, bw, kernel_type)
Estimate of cumulative distribution based on asymmetric kernel.


The available kernel functions for pdf and cdf are:

kernel_pdf_beta(x, sample, bw)
Beta kernel for density, pdf, estimation.

kernel_pdf_beta2(x, sample, bw)
Beta kernel for density, pdf, estimation with boundary corrections.

kernel_pdf_bs(x, sample, bw)
Birnbaum Saunders (normal) kernel for density, pdf, estimation.

kernel_pdf_gamma(x, sample, bw)
Gamma kernel for density, pdf, estimation.

kernel_pdf_gamma2(x, sample, bw)
Gamma kernel for density, pdf, estimation with boundary correction.


What Users are saying..

profile image

Abhinav Agarwal

Graduate Student at Northwestern University
linkedin profile url

I come from Northwestern University, which is ranked 9th in the US. Although the high-quality academics at school taught me all the basics I needed, obtaining practical experience was a challenge.... Read More

Relevant Projects

Machine Learning Projects
Data Science Projects
Python Projects for Data Science
Data Science Projects in R
Machine Learning Projects for Beginners
Deep Learning Projects
Neural Network Projects
Tensorflow Projects
NLP Projects
Kaggle Projects
IoT Projects
Big Data Projects
Hadoop Real-Time Projects Examples
Spark Projects
Data Analytics Projects for Students

You might also like

Data Science Tutorial
Data Scientist Salary
How to Become a Data Scientist
Data Analyst vs Data Scientist
Data Scientist Resume
Data Science Projects for Beginners
Machine Learning Engineer
Machine Learning Projects for Beginners
Datasets
Pandas Dataframe
Machine Learning Algorithms
Regression Analysis
MNIST Dataset
Data Science Interview Questions
Python Data Science Interview Questions
Spark Interview Questions
Hadoop Interview Questions
Data Analyst Interview Questions
Machine Learning Interview Questions
AWS vs Azure
Hadoop Architecture
Spark Architecture

Relevant Projects

Build an optimal End-to-End MLOps Pipeline and Deploy on GCP
Learn how to build and deploy an end-to-end optimal MLOps Pipeline for Loan Eligibility Prediction Model in Python on GCP
View Project Details
BigMart Sales Prediction ML Project in Python
The goal of the BigMart Sales Prediction ML project is to build and evaluate different predictive models and determine the sales of each product at a store.
View Project Details
Loan Default Prediction Project using Explainable AI ML Models
Loan Default Prediction Project that employs sophisticated machine learning models, such as XGBoost and Random Forest and delves deep into the realm of Explainable AI, ensuring every prediction is transparent and understandable.
View Project Details
Abstractive Text Summarization using Transformers-BART Model
Deep Learning Project to implement an Abstractive Text Summarizer using Google's Transformers-BART Model to generate news article headlines.
View Project Details
Build Portfolio Optimization Machine Learning Models in R
Machine Learning Project for Financial Risk Modelling and Portfolio Optimization with R- Build a machine learning model in R to develop a strategy for building a portfolio for maximized returns.
View Project Details
Image Segmentation using Mask R-CNN with Tensorflow
In this Deep Learning Project on Image Segmentation Python, you will learn how to implement the Mask R-CNN model for early fire detection.
View Project Details
Census Income Data Set Project-Predict Adult Census Income
Use the Adult Income dataset to predict whether income exceeds 50K yr based oncensus data.
View Project Details
Learn to Build a Neural network from Scratch using NumPy
In this deep learning project, you will learn to build a neural network from scratch using NumPy
View Project Details
Deploy Transformer-BART Model on Paperspace Cloud
In this MLOps Project you will learn how to deploy a Tranaformer BART Model for Abstractive Text Summarization on Paperspace Private Cloud
View Project Details
PyCaret Project to Build and Deploy an ML App using Streamlit
In this PyCaret Project, you will build a customer segmentation model with PyCaret and deploy the machine learning application using Streamlit.
View Project Details