k-Nearest-Neighbor Classifiers These classifiers are memory-based, and require no model to be fit. Given a query point x0, we find the k training points x(r),r = 1,...,k closest in distance to x0, and then classify using majority vote among the k neighbors.

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Distance measure for categorical attributes for k-Nearest Neighbor

For my class project, I am working on the Kaggle competition - Don't get kicked The project is to classify test data as good/bad buy for cars. There are 34 features and the data is highly skewed. I ...
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9 views

Find input image (ID,passport) in imagesDB based on similarity

I would like to decide if image is exists on DB images (pictures of IDs,passport,Stu. card,etc) I thought of KNN alghorithem that will plot the K closest images. Options for distance metric: 1) sum ...
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30 views

KNN Regression in R - using KKNN package [closed]

I have been trying to figure out how to plot a multiple regression for a training set with the K(KNN regression). The package name is KKNN for R. The line below expresses the multiple regression model ...
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19 views

Can we use kNN and k-mean at a same time?

I Get dataset of neighbours using kNN and then I want to apply k-mean on that dataset. By using this, is it possible that I get more accurate result? Is it logically correct that use kNN and then ...
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41 views

Are there optimization methods for k-NN parameter $k$?

Currently I am just go through from the min to the max, and determine $k$ by the performance. I am wondering if there's optimization approaches for selecting $k$? I am aware of there's question in ...
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Finding nearest neighbors using Jaccard distance for positive, real-valued vectors

Say we have $x_i, \ldots, x_n \in R ^ D$ with positive, real components and use Jaccard distance $$d(x_i, x_j) = 1 - \frac{\sum_{d = 1}^D\min(x_i^d, x_j^d)}{\sum_{d = 1}^D\max(x_i^d, x_j^d)}$$ to ...
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1answer
46 views

How to solve this problem on Curse of Dimensionality problem - Nearest Neighbours

I have started learning classification techniques and trying to solve the problems from the book Introduction to Statistical Learning. While currently working on the which is based on Curse of ...
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3answers
233 views

When should I apply feature scaling for my data

I started a discussion with a collague of mine and we started to wonder, when should one apply feature normalization / scaling to the data? Lets say that we have a set of features with some of the ...
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25 views

Binary classification with KNN

I post here because I don't know how to improve the performance of my binary KNN. The problem is that I have 99.8% Specificity and only 82% Sensitivity, but I'd rather have more Sensitivity than ...
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35 views

KNN - does it use centroids?

I'm really confused now having read so many articles on KNN, I can't help but think I'm missing the obvious. Let's say I have persons P1 and P2, P3 are represented with attributes of height, weight ...
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62 views

Is kNN best for classification?

I wanted to know if kNN might produce the best result for classification? Since, it is not model based, it does not loose any detail and compares every training sample to give the prediction. Hence ...
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15 views

Why SVM with RBF is similar to KNN with prototypes search?

I explored similar questions and everything I can see is that both kNN and RBF are non-parametric methods to estimate the density of probability of your data. However, I am not sure if this has ...
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25 views

How to use Similarity Measure in K-nearest neighbor Classification?

I have a similarity measure just like cosine. How can i use that similarity measure in traditional k-nn classification? Please provide some literature review (research papers) details which i should ...
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1answer
60 views

Excluding the scatter points from a feature

I have a set of data points that are supposed to sit on a locus and follow a pattern, but there are some scatter points from the main locus that cause uncertainty in my final analysis. I would like to ...
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1answer
34 views

Classification tips for a begginer

I'm doing a graduation work that involves applying Classification algorithms in a dataset of matches from Dota 2 (a popular MOBA game). Here's an explanation of the problem: Dota 2 matches are played ...
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13 views

Several categories using k-nearest neighbour

Is it possible to have a training data set for the k nearest neighbour with several categories likes 700 and about 10 attributes?
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2answers
115 views

Doing low-dimensional KNN on a large dataset

I have a simple two-dimensional dataset with columns X1,X2, and [outcome], and I want to try KNN (probably K around 100 or 1000, though ideally CV would be possible). The problem is that my dataset ...
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1answer
35 views

predict category by using K-NN algorithm having text features

I would like to predict the category of the provided data by using K-NN algorithm. Here is an example of the training data set ...
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1answer
36 views

Classifying a set of photos to places

I want to cluster photos and map them to places. As input I have Photos with locations (lat, long) Places - some as (imprecise) bounding boxes, some just as points, maybe others as bounding ...
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27 views

Method to select meaningful features for nearest neighbor classification

i try to perform some k nearest neighbor classification in R. That for i want to select the most meaningful features to deal with the curse of dimensionality. I have already decided to use Mahalanobis ...
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3answers
235 views

Does k-NN with k=1 always implies overfitting?

I found somewhere such statement, but on the other hand in some sources I found, that it is ok. What about risk of overfitting while using 1-NN in binary classification problem where explanatory ...
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1answer
69 views

advantage of euclidean distance for classification

Has euclidean distance any advantage in compare to another distance based methods like Manhatan distance or Maximum difference metric?
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2answers
193 views

Is KNN a discriminative learning algorithm?

It seems that KNN is a discriminative learning algorithm but I can't seem to find any online sources confirming this. Is KNN a discriminative learning algorithm?
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164 views

How to deal with unbalanced data

I'm doing data analysis with a dataset of 11795 data points (with 88 features). 85% (9973 points) of these data points correspond to data points belonging to class 1, 5% (589 points) belong to class 2 ...
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20 views

sample size to estimate the best k in kNN

I would like to use a kNN classifier. My data set is quite small and include 2 classes having about 200 samples each one. I need to estimate k by using a cross-validation approach. How many samples ...
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798 views

Why would anyone use KNN for regression?

From what I understand, we can only build a regression function that lies within the interval of the training data. For example (only one of the panels is necessary): How would I predict into the ...
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1answer
230 views

Pros of Jeffries Matusita distance

According to some paper I am reading, Jeffries and Matusita distance is commonly used. But I couldn't find much information on it except for the formula below ...
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2answers
61 views

Regression: what to do with categorical predictors?

I've got a few categorical predictors (like gender,...) and now I want to build regression models. So I've made the categorical predictors numeric by for example: "female" --> 1 and "male" --> 0. But ...
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54 views

Is this a correct interpretation of k nearest neighbours?

Given this dataset : name1,name2,distance a,b,1 a,c,5 b,c,8 If k=1 is the following correct : ...
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128 views

kozachenko-leonenko entropy estimation

I'm trying to implement the entropy estimation based on the closest neighbour from Kozachenko and Leonenko but I'm facing a problem I can't solve. The idea is to work in a new set ...
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2answers
54 views

Is this a valid use case for Euclidean distance?

I have a set of points which is a count of links that users have clicked on : ...
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1answer
30 views

Looking for measurement for nonlinear model

I use KNN regression to train out a model. The model estimates running time of a program based on different inputs, and the output is a single variable, which is time (double type). I want to ...
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34 views

Best way to classify a set through a single feature

I need to classify a single dataset through a numeric value. I added below a simple dataset to explain what I need. Restriction: Category has two values: 1 or ...
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49 views

What criteria are used to compare feature-based classification techniques?

When comparing feature-based classification techniques, what characteristics about the different processes should be considered? I'm comparing different classification techniques to try to figure ...
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99 views

Feature Selection for look alike modeling using k-NN

I have a list of items and various parameters for each items. For each item on my list i need to identify items which are similar to the item from my whole population . I am planning on using K-NN ...
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1answer
68 views

All nearest neighbors in high dimensional space

Suppose I have a very large binary matrix representing $n$ customers and the $m$ products they bought, with $n$ and $m$ both rather large (in the order of millions). The matrix is also pretty sparse. ...
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1answer
454 views

How to define the maximum k of the kNN classifier?

I am trying to use kNN classifier to perform some supervised learning. In order to find the best number of 'k' of kNN, I used cross validation. For example, the following codes load some Matlab ...
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209 views

Can the curse of dimensionality be solved by changing the metric tensor?

My (not too deep) understanding of the curse of dimensionality that affects a classification algorithm, such as k-Nearest Neighbor, is that at higher dimensions the 'sparsity' of euclidean space kicks ...
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1answer
144 views

How to interpret the number of k in k-nearest-neighbour classifier?

I have done some classification work using a k-nearest-neighbour classifier (kNN). And the classification performance is evaluated using cross-validation method. Some testing code from Matlab Help are ...
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145 views

regression with kNN on dataset with categorical variables

I am trying to train a regression model for dataset with 500k observations and 3 features. The features are categorical and have 50, 50 and 100 levels. Is (generally) kNN appropriate for this kind of ...
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62 views

Using KNN (with contributing weights) to calculate ranking

Sorry about the noob question, we tried looking through the answers but couldn't make sense of it. We are very basic with our math/stat knowledge, so please bear with us if this makes less relevant ...
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34 views

Implementation of prototype selection in application to nearest neighbor classifier

I am looking for an implementation of prototype selection algorithm and it is highly preferable that implementation would be in Python. I am using sikit-learn, but there is none.
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15 views

Increase Recall Rate for SIFT

Is there a better way to increase Recall Rate when using SIFT features? I am thinking a way to replace the NN1/NN2 ratio to account for slightly distorted objects. Moving towards clustering and using ...
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1answer
60 views

Using KNN for 2 Dimentional data

I am dealing with sentiment results of web articles. Sentiment is represented with two int values, +ve and -ve. For given article "xyz" I am getting different sentiments while testing at different ...
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329 views

How does knnimpute of the preprocess function work?

I am new to R and I use a script I do not completely understand. It preprocesses a dataset for data mining. At one point, the data (stored in fil) should be ...
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2answers
216 views

How to obtain the class conditional probability when using KNN classifier?

Using the KNN classifier, given a test data-point $x$, how do we get the probability of membership of $x$ to each class $y_i$, that is the probabilities $P(y_i | x)$ for $i = 1, 2, .., n$ (where $n$ ...
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199 views

Why is KNN not “model-based”?

ESL chapter 2.4 seems to classify linear regression as "model-based", because it assumes $f(x) \approx x\cdot\beta$, whereas no similar approximation is stated for k-nearest neighbors. But aren't both ...
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73 views

Using kknn regression function with NAs

I have been lurking here for awhile and now have a question I hope to get answered! I am wondering how to get nearest neighbor algorithms to deal with NAs most effectively. I am dealing with a data ...
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k nearest neighbors with repeated points

An example illustrates my question. Here I use the FNN package in R to find the indices of the 400 nearest points for each ...