Questions tagged [metric]

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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8 views

What metrics to use for scoring events' correlation? [closed]

we have the sensor data which is basically the event log, from three experimental sites as a site column. Here is how data looks like: ...
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measure of the difference between variation of two time series of probability distributions

I'm looking at a series of particle density probabilities of proteins floating on a cell, these particles move around and also blink, so these density probabilities differ a bit from one time to ...
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18 views

Sum R-Squared over uncorrelated features

I am currently developing an automatic approach to eliminate noisy samples from a data set. I clustered all the samples, and then I am iterating over all the clusters, eliminate the samples of the ...
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11 views

Bourgain Embedding and Supervised Learning

I would like to know how to approach the following problem: Suppose we have a labeled dataset (+-1) and we do Bourgain Embedding of this dataset after defining some "reasonable" metric between two ...
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28 views

Comparing survey data to passively measured data

Basic Situation: I have quite a large sample of around 10k people. In that sample I have two values for each person: a passively measured value of an amount of time, as well as their estimation of ...
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Are there any mathematical features that an evaluation metric must have?

I'm trying to optimize the hyperparameters of my model using the Bayesian approach with the hyperopt library. I have to code a ...
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20 views

Weighted averaging of multi-task (multi-output) regression errors

I am trying to elaborate a multi-task (multi-output) regression metric based on single-task metrics. From my perspective, it should be a weighted average of single-task errors estimated with the same ...
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1answer
36 views

Higher RMSE but lower MAE and RMLSE. Which model is better? [duplicate]

I am evaluating two machine learning models. The output is count data which has a range of 0 to 30, which most of the output values being small values. Large output values are rare. One model has ...
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1answer
15 views

Distance metric for sequential spatial data (routes navigated in 2d space)

I'm looking for a distance metric to compute how close certain paths taken by people navigating throughout a city are to a set of 'correct' routes. I have path recordings for some 'correct' routes ...
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Evalution Metric for Recommender with one Relevant Document

Suppose I have a bunch of user session data. For each user session, 5 rows are created. Each row contains the user id, item id and whether or not they selected that item. For example : ...
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1answer
26 views

What do P and Q refer to in the Minkowski distance?

Wiki gives some explanation and a figure about the Minkowski distance: The Minkowski distance is a metric in a normed vector space which can be considered as a generalization of both the ...
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26 views

Prediction model with lagged target variable as input

Including a lagged version of the target variable as input naturally improves the accuracy. A disadvantage I observe is that almost all the weight (e.g. in linear regression) is put on that feature, ...
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Coming up with a metric that measures “homophily”?

[I'm not sure if this question goes here on Stats.SE --- please move if not.] Consider a 2D unit square. I observe N red and M blue balls on the square. I want to come up with a metric that measures ...
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43 views

Is there a metric for data where only true positives are labeled (no true negatives)?

Let's say I have a dataset where each item is labeled with either (1) true positive or (2) unknown (could be true positive, could be true negative). It seems like if there are only true positives ...
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1answer
61 views

How to optimize MAPE in regression algorithms

I have a regression task where the label is varying from about 0.001 to 1000. One of the feature called group, for example, group A corresponding label from 0-0.1 and group G corresponding label from ...
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Does this statistical distance have a name and does the triangle inequality hold?

Let $P$ and $Q$ be two distributions on $\{1,2,\dots,n\}$. Define their distance by $$d(P, Q)=\Pr_{X\sim P,Y\sim Q}[P(X)Q(Y)>P(Y)Q(X)]\,,$$ where $X$ and $Y$ are independent. I could show that $d(...
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Weighting for precision and recall

I want to integrate the notion of weighting into an evaluation. I am wondering if it is appropriate/correct to calculate precision and recall scores by adding a weighting on true positives, false ...
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36 views

Can NDCG be used a metric for evaluating implicit feedback based recommender systems?

If we are using binary feedback then Can NDCG be used a metric for evaluating implicit feedback based recommender systems
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Non-metrics give “pathological” solutions: what does this mean?

In this set of slides on DTW, slide 25 says that we generally prefer metrics over measures because, "Non-Metrics can sometimes give pathological solutions when clustering or classifying data etc." ...
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Metric for ranked keyword identification

I am trying to determine which metric(s) to use to evaluate the "coverage" of several lexicons (lists of words) with respect to a ranked list of significant keywords I have extracted from two ...
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43 views

How can I weight categorical variables to create a user preference score?

Sorry, I'm not a statistician, but trying to fake it until I make it for data science. I'm working on a collaborative filtering algorithm, possibly paired with content-based similarity, for pairing ...
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41 views

Mahalanobis distance - vectors orientation?

In the Mahalanobis distance there are both $(\vec{x}-\vec{y})^T$ and $(\vec{x}-\vec{y})$. Which one is a column vector and which one is row vector? I need to write this in R, so vector orientation is ...
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1answer
73 views

Why is Pearson correlation is not an effective metric?

I found this statement in some documentation but I could not make sense of it. "Correlation is not a good metric for regression because it is scale and offset invariant". I understand that ...
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Set Similarity Measure that accounts for size

Suppose I have two sets, A and B where 10|A| = |B| and A is a subset of B. For the case where |A| = 1 the Jaccard similarity of the sets will be 0.1. For the case where |A| = 100 the Jaccard ...
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Comparing which histogram has overall low cost

Let's say there are two histograms which basically is constructed from array of numbers which is measured by, repeatedly performing a task by two different methods and individual numbers are time ...
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64 views

Is there a name for “normalized accuracy” as a statistic?

In short: I'm using a statistic representing the "normalized accuracy" of a confusion matrix. Is there a formal term for this? $$\text{normacc} = \frac{\text{acc}-\text{thacc}}{1-\text{thacc}}$$ ...
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Does Sørensen–Dice Coefficient (Dice Score) only account for true positives?

I'm working in a project on medical image segmentation which uses the Dice Score as part of the loss function, but I got some doubts with the commonly adopted implementation. The definition of Dice ...
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Difference between Euclidean ,Pearson, Geodesic and Mahalanobis distance metrics

Given a set of samples $X$. We are tasked to find an appropriate distance metric for $X$ from the given options which are Euclidean Pearson Geodesic and Mahalanobis distance metrics. To solve this, ...
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49 views

Clustering data with covariance for each point

I am looking to cluster data points that each have a covariance around itself (based on some function of its neighbourhood, but how I got it is not important). I would like to use the covariance to ...
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1answer
121 views

ROC-AUC score in sklearn

I'm trying to understand ROC-curve and AUC characteristic for it and found that behaviour of sklearn function roc_auc_score ...
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24 views

Is there a difference between Hausdorff Distance and Discrete Frechet Distance when working on time series?

I'm currently doing a little research on which kind of distance metric is the best for comparing the time-series I'm working with. To be clear, I'm doing this for a computer science internship, and I ...
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127 views

Why am I getting r2_score on test set as negative?

I wanted to initally test out without dropping any features (Redundant features such as ID are dropped). data_source -> https://archive.ics.uci.edu/ml/datasets/Automobile This was my procedure: 1) ...
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1answer
21 views

Creating a custom metric based on diverse feature scalse

I would like to create a custom metric that takes into account multiple features and produces a certain score. However, the issue is that I have data that has many different data types, such as ...
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Distance / Metric between two regression models? [closed]

I wonder if there is any theory or work about the "similarity" of two regression models. For example, if it is linear regression, the "similarity" could be defined by the l-2 distance between the ...
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25 views

Multiclass classifier with undefined prediction, how to calculate metrices

I build a multiclass classifier. I want the classifier to predict a few samples with little false positives, rather then many samples with lots of false positives. Therefore I want to choose a ...
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Metrics for comparing a multi-class model vs. a multi-label model?

The dataset is a multi-label dataset, where each item can have more than one labels. I first trained a multi-class classifier by randomly select the label for each item at each iteration, and ...
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Computing and estimating the EER on an entire dataset

I have reproduced "Generalized End-To-End Loss For Speaker Verification". It describes a method to create a deep learning model that can derive an embedding (a vector of 256 float values) that ...
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How do you / can you compare Bayesian vs. frequentist regression models?

I am working on a regression model to predict a target variable in a dataset with over 100 features. Three different regression models are defined and fit in order to compare their performance using $...
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39 views

Replacement for angular distance metric

I am looking for a distance metric that could be used instead of cosine/angular distance for high dimensional data. Metric that is limited the same way as cosine/angular distance is would be great. ...
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24 views

Consistency metric explanation

I am trying to understand a bit more about the consistency metric (to understand how consistency-based subset evaluation works). I find on this paper the following equation : $$\text{Consistency}_s =...
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1answer
253 views

Suitable performance metric for an unbalanced multi-class classification problem?

I have an unbalanced multi-class classification problem with the following class distributions: Class 0: 17.1% Class 1: 63.2% Class 2: 19.7% I am using scikit-...
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Mahalanobis: Covariance or correlation? [duplicate]

Is the Mahalanobis distance using correlations or covariances (among two vectors) to determine the similarity? I know that both are quite the same and differ only by a division of a standard deviation ...
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10 views

Which performance metric to use for stratified data? [duplicate]

I'm trying to classify a data into 3 classes (supervised), one of which is heavily underrepresented in the data set. In order to combat this imbalance, I decided to stratify the data. Now I want to ...
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1answer
29 views

Is recall a relatively meaningless metric in a balanced dataset?

Just looking for a sanity check here. Leaving aside precision, is talking about the recall of a binary classification algorithm sensible where 50% of the cases presented to it are positive and 50% ...
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Machine learning: eval_function for multiclass classifcation

I have checked What are the measure for accuracy of multilabel data? but I think the discussion somehow confused between loss and evaluation function. Say I have a multi-class classification problem ...
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2answers
72 views

Metrics for unbalanced classes [duplicate]

I have been looking for good metrics on this data set I am working, however it is highly unbalanced. It has a total of 8 categorical classes, one of them is responsible for ~40% of data, another for ...
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2answers
41 views

Localized distance function on sequential binary data

I am trying to find a good distance function for sequential data that is all binary. For now, I am using Edit distance however I have some more domain-specific knowledge that I would like to ...
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24 views

Quality metric of sampled time series data

I have a time series that has too many points. I sample one in every 100 points, in order to reduce the amount of data I need to transmit from my measurement device. What accuracy metric can I use ...
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296 views

Imbalanced Test Data

I have an imbalanced (1:5) training and test set with only two classes and have oversampled the training set with SMOTE so that the class ratio is 1:1. The ML model gives values over 0.7 for accuracy, ...
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Measure for evaluating a generated ranking of items, when best k items are known

I am evaluating different kinds of feature selection algorithms. Some return a ranking of variables based on their usefulness (to predict a target variable, etc.). Lets say there are n variables in ...