How to do Kernel regression by hand in Python .Kernel Regression in Python

This notebook demonstrates how you can perform Kernel Regression manually in python. While Statsmodels provides a library for Kernel Regression, doing Kernel regression by hand can help us better understand how we get to the find result.

First, I will show how Kernel Regression is done using Statsmodels. Next I will show how it is done by hand, then finally overlay both plots to show that the results are the same.

To begin with, lets looks at Kernel regression by Statsmodels

We generate y values by using a lambda function. You can change the lambda function around to see what happens. The x values i.e. the independent variable is controlled by `new_x`

where we have displaced the x value to show that you can have

```
import numpy as np
import plotly.express as px
from statsmodels.nonparametric.kernel_regression
import KernelReg as kr
import plotly.graph_objs as go
import pandas as pd
```

```
np.random.seed(1)
## xwidth controls the range of x values.
xwidth = 20
x = np.arange(0,xwidth,1)
## we want to add some noise to the x values so that dont sit at regular intervals
x_residuals = np.random.normal(scale=0.2, size=[x.shape[0]])
## new_x is the range of x values we will be using all the way through
new_x = x + x_residuals
## We generate residuals for y values since we want to show some variation in the data
num_points = x.shape[0]
residuals = np.random.normal(scale=2.0, size=[num_points])
## We will be using fun_y to generate y values all the way through
fun_y = lambda x: -(x*x) + residuals
```

Applied Data Analysis in Python - Machine Learning and Data science. Machine learning in Python. This course at the University of Bristol covers scikit-learn, fitting, correlation and clustering.

ðŸ”µ Intellipaat Data Science with Python course: https://intellipaat.com/python-for-data-science-training/In this Data Science With Python Training video, you...

Applied Data Analysis in Python Machine learning and Data science, we will investigate the use of scikit-learn for machine learning to discover things about whatever data may come across your desk.

PySpark in Machine Learning | Data Science | Machine Learning | Python. PySpark is the API of Python to support the framework of Apache Spark. Apache Spark is the component of Hadoop Ecosystem, which is now getting very popular with the big data frameworks.

Practice your skills in Data Science with Python, by learning and then trying all these hands-on, interactive projects, that I have posted for you.