Questions tagged [k-nn]

K-Nearest Neighbor (K-NN) is a classification algorithm that determines the label of some data point based on the most common label of the closest k other points.

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1answer
24 views

Varying the number of neighbors in nearest-neighbors regression

For nearest-neighbors regression, it is plausible to increase the number of neighbors used to predict $f(x)$ when there are many data points near $x$. What is a good algorithm for varying the number ...
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1answer
19 views

Has this paper used weighted KNN or not?

Please tell me if you see this paper in the link below has used weighted KNN? because they have used weights as the training and testing samples and no formula written. They don't explain the ...
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1answer
31 views

Ball Tree and Pseudometrics

The docs for sklearn.neighbors.DistanceMetric state that in order to be used within the BallTree, the distance must be a true metric (i.e. be non-negative, 0 ...
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0answers
44 views

What does big O mean in KNN optimal weights?

Wiki gives this definition of KNN In pattern recognition, the k-nearest neighbors algorithm (k-NN) is a non-parametric method used for classification and regression. In both cases, the input ...
2
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1answer
43 views

values passed to user-defined distance function by KNeighborsClassifier is wrong

I have a data-set in which all features are binary and the class of each data-point is also binary. I am trying to use KNearestClassifier with a user-defined distance function as follows: ...
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1answer
45 views

How to predict the value in KNN?

I am trying to build the KNN algorithm for IRIS dataset. First, I've computed the distance and stored it in 1d array. However, I am really struggling to build the prediction function. Therefore two ...
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1answer
30 views

Is the distance in Nearest Neighbors a good measure of similarity?

Let's train a Nearest Neighbor model with just one sample in it: In [48]: nn = NearestNeighbors().fit([[0, 1, 0, 0]]) So this one sample has just one significant ...
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1answer
46 views

Machine Learning algorithm for detecting anomalies in large sets of events

Let's start with the following hypothetical preconditions: There is traffic: normal and anomaly. Each traffic sample contains a list of events (of variable size) Events happen in order, the possible ...
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1answer
38 views

Item-based recommender using K-NN

I'm trying to build an item-based recommender using k-nn. I have a list of items, all of which have some properties (features) in common. ...
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1answer
48 views

What is the Value of X in KNN and Why? [duplicate]

I have a dataset of 25 instances these instances are divided into 2 classes Green Circles and Blue Squares data distributed as this graph I want to predict X's class based on "Likelihood Weighted ...
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1answer
66 views

logic behind weighted KNN

I am reading about KNN So I made another example to make things clearer In this example (Image attached) You can see there are in total 5 Greed Circles and 20 Blue Squares by standard KNN (k=3) , ...
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1answer
21 views

adding a supervizing process during knn process

I try to improve my knn regression process (I use sklearn / python, but it doesn't matter). Because I can have a scientific point of view on my data, I would like to improve my results. I give you an ...
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1answer
20 views

learning a distance metric from the output of a knn output

Suppose that someone has trained a nearest-neighbor algorithm based on some unknown metric. I have a large dataset of $N$ observations, and $P$ features. For each observation I am given $K$ indices ...
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1answer
47 views

KNN RandomizedSearchCV typerror

While trying to study a binary classification problem with KNN and trying to tune the parameters of the model I'm getting a typerror that I quite don't understand. Is a parameter missing or something? ...
2
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1answer
38 views

Mapping of categorical features into binary indicator features

I am currently reading an introductory machine learning book by Daumé (ch. 03, p. 30) and when discussing the mapping of categorical features with "n" possible values into "n" binary indicator ...
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1answer
18 views

Does it make sense to use KNN to target ticket buyers for arts events?

I work for a medium-sized non-profit. We have a database with approximately 40,000 profiles of folks (mostly patrons). For each show a patron attends, we add an attribute that indicated that they're ...
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4answers
326 views

How to save a knn model?

I need to save the results of a fit of the SKlearn NearestNeighbors model: knn = NearestNeighbors(10) knn.fit(my_data) How do you save to disk the traied ...
2
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1answer
47 views

Coordinate System's influence on $L$ distances (Manhattan and Euclidean)

I don't understand this picture, which says if we change the coordinate system, we would have the same result for $L_2$ distance, whereas, our result would differ for $L_1$ distance. What does it ...
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0answers
39 views

How do I avoid time leakage in my KNN model?

I am building a KNN model to predict housing prices. I'll go through my data and my model and then my problem. Data - ...
2
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1answer
46 views

K-Nearest Neighbours algorithm explanation needed

I need some explanation for K-Nearest Neighbors algorithm. Why is the training process needed in KNN algorithm? In regression models the training process means to find optimum parameters for a ...
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1answer
39 views

Normalization(minmax) gives me worse results than before in KNN, follow up actions?

Hello I'm studying a classification problem with KNN right now. I have many numeric features that I normalized with MinMaxScaler, I also got some OHE categorical features that not seem to cause the ...
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1answer
45 views

Can `k=1` be a good choice for K neighbors classification?

Running sklearn.KNeighborsClassifier() on Kaggle's Leaf Classification sample (set of 99 species, 10 specimen each), with defaults kNN parameters and a grid search ...
3
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1answer
71 views

K Nearest Neighbour with different distance matrix to each datapoint

I'm wondering if there is library support in python (such as sklearn) for doing KNN on a data set that has a custom distance matrix (positive definite) for each data point (x is a query point, $x_i$ ...
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0answers
48 views

Is there an algorithm that imputes missing values based on n nearest columns? (KNN hybrid)

I have a dataset of 70 columns that have missing values. Each column has a few columns (3-5) that it is significantly more correlated than the others but each column's correlated columns are very ...
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2answers
124 views

Choosing k value in KNN classifier?

I'm working on classification problem and decided to use KNN classifier for the problem. so if k=131 gave me auc of 0.689 and k=71 gave me auc of 0.682 what should be my ideal k? Does choosing ...
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1answer
26 views

Date transformation for KNN to get distance [duplicate]

I have data set with date features like 01/01/2019 and I would like to use KNN. However, I cannot find a good transformation for dates that has a meaningful distance result for the last feature. For ...
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2answers
64 views

Date transformation for KNN

I have data set with date features like 01/01/2019 and I would like to use KNN. However, I cannot find a good transformation for dates that has a meaningful ...
6
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1answer
83 views

How to decide how many n_neighbors to consider while implementing LocalOutlierFactor?

I have a data set with rows: 134000 and columns: 200. I am trying to identify the outliers in data set using LocalOutlierFactor from scikit-learn. Although I ...
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0answers
232 views

Training anomaly detection on text string [closed]

I have text string stored in a column, resulting after pre-processing of web traffic data. Now I want to apply anomaly detection on it and for that purpose I applied ...
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0answers
20 views

Neighbourhood based approach on implicit feedback datasets

Is it possible to use a neighbourhood-based approach on implicit feedback dataset? I have a dataset with information about how many times a certain item was viewed by a particular user. I know that MF ...
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0answers
11 views

approximate k-nearest neighbours with LSH

I m studying LSH and one question of my book say that with LSH we can reproduce an approximate K-NN algorithm. I m thinking on, and I just have this idea: Hash all element of the data Check the ...
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1answer
329 views

Scaling label encoded values for Linear Algorithms

I have encoded categorical variables to numerical values. As we know that for feeding values to Linear Algorithms like SVM or KNN, we scale the values for columns having large variations. I have ...
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3answers
47 views

A metric between trees

I have certain tree structures. I am not an expert in machine learning. As I would with take KNN, I would calculate distances via metric function and a new data point and the points from the training ...
0
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1answer
264 views

Why do I not get 100% Accuracy with KNN with $K=1$

I am playing with KNN on the Iris Dataset I expected to get 100% accuracy with $K=1$ since every point should predict itself based on the Voronoi volume around it created by the KNN algorithm. ...
3
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2answers
55 views

Regression for discrete values?

Im a noob in ml / statistical algorithm, but I do have worked with simple classifiers and regression I like some opinions if I am going the right way, given my limited knowledge My problem is ...
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0answers
227 views

ValueError: operands could not be broadcast together with shapes (140,) (10230,)

I wrote this code for emotion recognition using EEG data. I am performing feature extraction by finding mean and standard deviation and performing classification using Knn algorithm. I am getting this ...
0
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1answer
231 views

How to handle date data for Knn?

I'm working on a project about predicting kickstarter project success(classification) and my dataset has many columns that could be used as features such as : state_changed_at, launched_at, ...
2
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1answer
2k views

How Does Weighted KNN Work?

I am reading notes on using weights for KNN and I came across an example that I don't really understand. Suppose we have K = 7 and we obtain the following: Decision set = {A, A, A, A, B, B, B} If ...
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2answers
2k views

Features selection in KNN

I have a naive question about using the K Nearest Neighbor algorithm: is feature selection more important in KNN than in other algorithms? If a particular feature is not predictive in a neural ...
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2answers
317 views

How can I implement tangent distance for k-nearest neighbor in python/scikit-learn?

My ultimate aim is to have a function which I can feed into scikit-learn's NearestNeighbor class as a custom metric parameter. ...
2
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1answer
266 views

How does KNN work if there are duplicates?

I am currently debating with my friend about how KNN handles duplicates. Suppose K = 2, and we have a 1-dimensional set of data points to illustrate my dilemma I = {1, 2, 2, 2, 2, 2, 6} Thus is it ...
0
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1answer
91 views

Is there any way of ordering/sorting vectors?

I am working on KD-Tree for nearest neighbor algorithm, where at each level of the tree we arbitrarily choose a dimension to cut upon and sort the points based on that chosen dimension value, after ...
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0answers
20 views

Best way to find dissimilarity in a 6x2 DataFrame?

I'm new to data science and am currently learning different techniques that I can do with Python. Currently, I'm trying it out with Spotify's API for my own playlists. The goal is to find the most ...
0
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1answer
41 views

Is there an upper bound for k in nearest neighbors-based methods?

When applying a nearest neighbors-based method to a data of, for instance, 2000 points, what is the largest number of neighbors that can be considered ? I am using a nearest neighbors method in an ...
2
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1answer
40 views

Creating a single number from a numpy array - Python [closed]

I am working on a gender classification project. I am extracting the pixels of an image using a Numpy array in Python, similar to the one below: ...
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1answer
41 views

Problem with calculating error rate for KNN

I am trying to validate the accuracy of my KNN algorithm for the movie rating prediction. I have $2$ vectors: $Y$ - with the real ratings, $Y'$ - with predicted ones. When I calculate Standard ...
3
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2answers
30 views

Why isn't local averaging (including KNN) used often for regression?

My professor said that the "holy grail of regression" is the function E(Y|X=x) i.e. the conditional expectation of Y on X. In practice, you'd take a small window of X and take the average value of Y ...
7
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1answer
57 views

How to decide the shape of input features, when each data file is of different length?

To help me understand the benefits and shortcomings of decision trees, KNN, Neural Networks, ...
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2answers
143 views

Taking Neural Network's false positives as the recommendation system result?

I am creating a recommendation system and considering two parallel ways of formalizing the problem. One classical, using proximity (recommend the product to the customer if a majority vote of 2k+1 ...
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0answers
27 views

How to determine the k in kNN [duplicate]

I'm looking to use the k-Nearest Neighbors (kNN) algorithm. What are the possible methods for determining the best K? From what I have read, looking at many different values(say 10-100) should work, ...