Understanding Limits of a Kernel Function

In summary, the kernel function K_delta(x) has a limit that does not exist as delta approaches 0. This is because for different values of x, the limit is different, which means it does not satisfy the definition of a limit. This is due to the lack of restrictions on x, causing the function to have two different limits instead of one.
  • #1
latentcorpse
1,444
0
I have a problem with my notes that I can't understand.

They say:

For the kernel function [itex]K_{\delta}(x)=\frac{1}{\sqrt{2 \pi \delta}} e^{-\frac{x^2}{2 \delta}}[/itex] for [itex]\delta>0[/itex],

we have as [itex]\delta \rightarrow 0+ , K_{\delta}(x)= \infty[/itex] if [itex]x=0[/itex] and [itex]K_{\delta}(x)= 0[/itex] if [itex]x \neq 0[/itex].

therefore [itex]\lim_{\delta \rightarrow 0} K_{\delta}(x)[/itex] does not exist.

doesn't this contradict itself? it says the limit doesn't exist but in the line before it just said what the limit was?
 
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  • #2
The limit only exists if you exclude x=0, which you don't. It's not a contradiction because they show that for different values of x you get different limits so the limit delta->0 does not exist for all x.
 
  • #3
why does the limit not exist if we include this point though?

is it because the limit of something can't be infinity (surely not?)

or is it because the limit of something can't be two different things (although i though this would have been ok too)

or is it because the limit isn't continuous?
 
  • #4
No, it's because the limit doesn't exist. No function satisfies the definition of "limit of K_delta(x) as delta approahces 0".
 
  • #5
They don't put any restrictions on x, which causes the function to have two different limits. For it to exist it should have the same limit for all possible values of x.
 

1. What is a kernel function?

A kernel function is a mathematical function that transforms data from its original form into a higher-dimensional space. It is typically used in machine learning and data analysis to make data more easily separable and to improve the performance of algorithms.

2. What are the limits of a kernel function?

The limits of a kernel function refer to the maximum and minimum values that the function can produce. These limits are determined by the mathematical properties of the function and the data it is being applied to. Understanding these limits is important for evaluating the performance and accuracy of a kernel function.

3. How do you determine the limits of a kernel function?

The limits of a kernel function can be determined by analyzing its mathematical properties, such as its range and domain, as well as its behavior at extreme input values. Additionally, the limits can be estimated by testing the function on a variety of data sets and observing the maximum and minimum values it produces.

4. What factors can affect the limits of a kernel function?

The limits of a kernel function can be affected by various factors, including the type of data it is being applied to, the complexity of the function, and the parameters used to define the function. Additionally, the choice of kernel function itself can have a significant impact on the limits.

5. How can understanding the limits of a kernel function improve data analysis?

Understanding the limits of a kernel function can improve data analysis by providing insights into the accuracy and reliability of the results. By knowing the maximum and minimum values the function can produce, researchers can better evaluate the validity of their findings and make more informed decisions about the use of a particular kernel function.

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