Ask Ghassem - Recent questions tagged knn

How to perform a classification or regression using k-NN?

Thu, 27 Jun 2019 02:54:42 +0000

Suppose, you have given the following dataset where x and y are the 2 features and color Red or Blue is the target variable.

a) A new data point $x=1$ and $y=1$ is given. Using Euclidean distance in 3-NN, what you predict as the color for this data point?

Dataset
x	y	Color
-1	1	Red
0	1	Blue
0	2	Red
1	-1	Red
1	0	Blue
1	2	Blue
2	2	Red
2	3	Blue

b) Now assume we have the following dataset and the target value is the price. A new data point $x=1$ and $y=1$ is given. Using Euclidean distance in 3-NN. What would be the estimated price?

Dataset
x	y	Price
-1	1	$100
0	1	$50
0	2	$20
1	-1	$40
1	0	$30
1	2	$40
2	2	$70
2	3	$30

Calculate k nearest points using kNN for a single D array

Mon, 01 Oct 2018 21:50:03 +0000

I am not able to figure out how the calculation of the $m$ nearest points will be in a single dimensional array using kNN. Can anyone offer a clue or example?
Thank you

K Nearest Neighbor (KNN) - includes itself

Mon, 01 Oct 2018 21:35:01 +0000

The KNN function in the sklearn library (when coded properly), outputs the points closest to p based on the value of k, and others.

The point(s) would include itself when the code does not consider the point is in the data set.

I included codes to exclude and include this occurrence.

Is this acceptable?

What happens as the K increases in the KNN algorithm ?

Fri, 28 Sep 2018 01:39:08 +0000

I am wondering what happens as K increases in the KNN algorithm. It seems that as K increases the "p" (new point) tends to move closer to the middle of the decision boundary?

Any thoughts?

How is KNN different from k-means clustering?

Thu, 27 Sep 2018 05:25:34 +0000

Is normalization necessary in all KNN algorithms? (Python)

Thu, 27 Sep 2018 01:06:02 +0000

I have read online articles involving KNN and its emphasis on normalization. I would like to know if all KNN functions in Python need to involve normalization?

I do know that normalization computes values that are usually between 0 and 1 but would this process be necessary in all python KNN functions or is it specific to certain scenarios?

When dealing with distance, L1 or L2, would normalization be needed?

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