Tagged Questions

A metric is a function that outputs a distance between 2 elements of a set & meets certain strict criteria (some 'distance' functions are not metrics).

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Clustering inertia formula in scikit learn

I would like to code a kmeans clustering in python using pandas and scikit learn. In order to select the good k, I would like to code the Gap Statistic from Tibshirani and al 2001 (pdf). I would like ...
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Metric warning using caret's rfe

I am using the caret package to do feature selection with rfe while training a knn ...
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Metric for nearest neighbor method

Is there a requirement that the measure used in Nearest Neighbor methods be a proper metric distance? What will happen if I use an arbitrary function (e.g., one that does not satisfy the triangle ...
181 views

Measuring the smoothness of time series

I work on a method that gives a (noisy) estimation of brain volume over time in Alzheimer's patients. As we know that the evolution is smooth and even mostly linear if looked at over a time frame of ...
71 views

Finding the highest probability balls

I'd appreciate any insights or references to research regarding the following: Suppose you have a discrete metric space with a probability distribution on it. also, suppose that I'm given a number ...
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Looking for metric to measure linear and constrained relationship between 2 variables

Data are 2D x-y pairs, both of which have [0-1] possible range. I need to calculate how well these data fit a linear relationship, where the intercept is 0 and the slope is 1. In other words, a ...
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Symmetrised Kullback - Leibler divergence

I have trouble understanding KL divergence, where P is probability mass function of true distribution of data and Q is the approximation of P. The definition of KL divergence is: ...
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Verifying the output of implementing internal clustering validity indexes

I have implemented some internal clustering validity indexes in Java: Simplified Silhouette. Calinski-Harabasz (VRC). Davies -Bouldin. Dunn's Index. How could I verify if my implementation is ...
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How to measure the distance between two Bayesian networks?

Given a set of random variables $\{X_1, X_2, \dots, X_M \}$ and a (complete) dataset $D$, I have used some standard (greedy) algorithms to find good candidates to be the "true" bayesian network ...
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Generalized RBF Kernels

There is the notion of Generalized RBF Kernels, for example in "Towards Optimal Bag-of-Features for Object Categorization and Semantic Video Retrieval" from Jiang (1) or in formula (2.72) in ...
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Metrics for covariance matrices: drawbacks and strengths

What are the "best" metrics for covariance matrices, and why? It is clear to me that Frobenius&c are not appropriate, and angle parametrizations have their issues too. Intuitively one might want ...
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Recall and precision in classification

I read some definitions of recall and precision, though it is every time in the context of information retrieval. I was wondering if someone could explain this a bit more in a classification context ...
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When should I prefer kappa over accuracy for binary classification problems?

I'm using the caret package in R that provides two kind of metrics for classification problems - accuracy and kappa. When should ...
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How do you compare two Gaussian Processes?

Kullback-Leibler divergence is a metric to compare two probability density functions, but what metric is used to compare two GP's $X$ and $Y$?
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Is the square root of the symmetric Kullback-Leibler divergence a metric?

It is well known that the square root of the Jensen-Shannon divergence is a true metric, but how about the square root of symmetric KL: D(P||Q)+D(Q||P)? I have reasons to believe that it also is a ...
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How to integrate edit operations to TF/IDF weighting scheme

Is there a way to integrate edit operations into TF/IDF weighing scheme in order to assign accurate weight to poorly typed tokens?
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Duplicate detection/classification using TF/IDF and cosine similarity metrics

I am working on text classification using TF/IDF and cosine similarity metrics. In computing the similarity between two records (objects) in a database, TF/IDF assigns weight vector for each record by ...
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Combining tf/idf with a similarity metric ie edit distance, affine gap of jaro winkler [duplicate]

I am working on combining TF/IDF with a similarity metric such as edit distance, affine gap or jaro-winkler in order to improve its effectiveness. Thanks in advance for your response.
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metric on voting data

I'm studying computer science but am lost with statistical methods. An algorithm I've been studying needs a formal metric on the space of our data set. Our data set can be described as `voting data'. ...
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Distance metric for survival functions?

Similar to this question, I would like a good metric for the distance between multiple ecdfs. However, in this case I have survival functions that are right-censored. Question Is there a metric ...
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Multidimensional scaling on distance or similarity matrix

Why doesn't the scatter plot change when I perform multidimensional scaling on distance or similarity matrix? This figure uses similarity matrix And this figure use distance matrix ...
287 views

Convert similarity matrix to dissimilarity

What is the equation to convert from similarity matrix to distance matrix? The similarity matrix uses some "perceptual" metric(from psychology) so it's a little bit different. Can I just use inverse ...
226 views

k-means and different metrics [duplicate]

In presentations of k-means to compute the centroid of a new cluster the Euclidean average seems to always be used. If the similarity metric used is not the Euclidean metric it seems to me this other ...
224 views

What are the use cases related to cluster analysis of different distance metrics?

I'm trying to use different distance metrics like Euclidean, Manhattan, cosine, chebyshev among other distance metrics in my k-means algorithm to calculate distances between the data points and the ...
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Which metric use for problem of clustering spatial data of wind direction and speed?

I have two dimensional spatial (x,y - coordinates of meteo stations) data for small region (so I could neglect the shape of earth globe), for each (x,y) I have one observation of wind direction and ...
236 views

Metric and Clustering Method

I need some suggestions regarding what kind of metric and clustering analysis I should use. I read a lot of posts but didn't get any hints about this type of data. I have a 3000*5000 matrix, where ...
86 views

What is meant by the term “formal distance metric”?

I am familiar with the idea of metrics in software and I know something about using distance functions in clustering, but I don't really know what is meant by "formal distance metric". What is the ...
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Comparing clusterings: Rand index vs variation of information

I was wondering if anybody had any insight or intuition behind the difference between the Variation of Information and the Rand Index for comparing clusterings. I have read the paper "Comparing ...
479 views

Is the absolute value of distance covariance a metric?

I'm reasonably certain the absolute value of the distance covariance satisfies d(x, y) ≥ 0 (non-negativity, or separation axiom) d(x, y) = 0 if and only if x = y (identity of ...
1k views

Gower's dissimilarity index

I would like to ask a question about Gower similarity/dissimilarity index. Is it ok to use the Gower dissimilarity measure with Ward linkage clustering? I was reading that the Gower similarity index ...
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Distance metric and curse of dimensions

Some where I read a note that if you have many parameters $(x_1, x_2, \ldots, x_n)$ and you try to find a "similarity metric" between these vectors, you may have a "curse of dimensioality". I believe ...
309 views

Metric for probability based classification

I am doing a system for classifiying documents. The project demands the use of probability based output. So a sample will have a probability for belonging to each class. For now I use logistic ...
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Does a distance have to be a “metric” for an hierarchical clustering to be valid on it?

Let us say that we define a distance, which is not a metric, between N items. Based on this distance we then use an Agglomerative hierarchical clustering. Can we use each of the known algorithm ...
420 views

Metric to compare models?

Using R, I have developed three models: linear regression using lm(); decision tree using rpart(); k-nearest neighbor using ...