Questions tagged [ranking]

Ranking is the task (for respondents) or the result of ordering the given stimuli or performers from "highest" to "lowest" (or *vice versa*) in some respect. It is usually contrasted with rating of stimuli. (For ranking as a way of data transformation - use tag [ranks]).

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Testing similarity of rank orders

Are there any statistical tests for the similarity of rank orderings? E.g. suppose 4 students a, b, c and d take a test 5 times over a period of 5 months, and each month we rank the students' scores: ...
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Compromise between ranked and kernel-based estimate of empirical distribution (for estimating likelihood of single value)

Setup I have: About fifty values $x_1,…,x_n$ sampled from the same but unknown distribution $X$. I have no useful theoretical insight on the nature of that distribution. Empirically, the distribution ...
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Different Number of Judges Scoring and how to Rank

I have looked everywhere and I am struggling to find a solution. Granted, I am no statistician but I do have some knowledge of basic statistics. Any help is truly appreciated! There are a number of ...
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Ranking categories by value in specific percentile

Is there a name for ranking categories by their value in a specific percentile (e.g., 33th percentile)? A fictitious example: Goethe published 9 books, Schiller published 7, and Herder published 3. We ...
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What is the points valuation for this problem (assuming that 5-pointer worth 1 point is standard)?

Given four teams in a tournament, they versus against all the other teams once for each to reach the best-possible place. Three points are awarded to the team winning a match, with no points awarded ...
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Comparing objects with mostly unknown parameter values

Imagine that you have a picture of an apple and a picture of grapes. You need to decide what picture has the higher contrast. You know that there should be a significant enough difference between the ...
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Hierarchical ranking/clustering algorithm?

Consider two situations: 1st situation You ordered a number of cubes by their weight (from light to heavy). Then you notice that most of the cubes are grey, but there're a lot of the cubes with ...
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computing sequence from subset of nodes

Given $N$ sequences of codes $$ c_1 \rightarrow c_3 \rightarrow c_2 \\ ... \\ c_3 \rightarrow c_5 \rightarrow c_7 \rightarrow c_8 \rightarrow c_1 $$ where the codes are from set $\psi = \{c_1, c_2, ....
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asking humans to rank items

I have around 50 items and I need to ask human graders to rank them. Is there any good resource on how to design this crowd sourcing task? For example, it will be tiresome to ask humans to rank 50 ...
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Should 3-pointers be worth 2.5 points?

I was seeking an alternative scoring rule sets instead of three points for a win (gained more engaging and balanced) to cancel the theory "Banking a draw meaning a new kind of loss". It's ...
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Looking for a way to analyse results of a poll and compare them to expected results

I will be conducting a poll on 5 to 10 people. I will have each of them score about 100 samples from 0 to 10 and then I will compare their answers with the expected values of those samples. I am ...
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What is the best statistical test for correlation between 2 ordinal variables? [duplicate]

"1st variable is ranking 2nd is Likert scale I am to correlate the motivation scale (Likert) to job preference (ranking)"
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Ranking probabilities of logistic regression models M1 and M2 taking confidence intervals in account

I have two models M1 and M2 and each models the probability of having cancer with logistic regression. M1 is based on independent variables IV1 measured on a given sample of individuals and M2 is ...
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Machine learning tends to produce poorly-calibrated classifiers, but are the class ranks still valid?

In classification problems, "non-probabilistic" machine learning models such as boosted trees, neural networks, etc. are known to produce poorly-calibrated class scores, which aren't ...
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Cluster confidence scoring

I have a scenario where I am provided a list of clusters and pairwise distance only between items in same cluster. I need to rank these clusters based on some kind of relative score from this info. e....
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Generalize Kendall tau distance to ordered groups?

If we have two ordered lists, e.g., A=[1,2,3,4,5], B=[3,5,4,2,1], then we could use Kendall tau distance (which is 0.8) to ...
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What are the statistically relevant patterns among 25–18–15–12–10–8–6–4–2–1? Models used?

Here is the current Formula One World Championship points scoring systems— https://en.wikipedia.org/wiki/List_of_Formula_One_World_Championship_points_scoring_systems#Points_scoring_systems Currently ...
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Quantifying agreement of ordinally ranked sequences

I've been using a very particular set of closely related metrics to quantify how well two ranked sequences agree with one another. I'd like to know if this way of thinking is well-known and if any of ...
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Statistical test for recommendation algorithms

I've developed 2 different image based recommendation systems for an e-commerce company and now it's time to evaluate them using some statistical tests. Both algorithms work in a way in which if fed ...
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Deriving Overall score from global and personalised score

I am working on developing a ranking function that will emit a score for different metrics of interest. For a particular user, we sort the scores to find out important metrics, and action items are ...
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How to determine the probability of a player getting 1st in a game, given win probabilities of head to head matchups of players?

I have predicted the probability that player A beats player B in a head to head matchup in a game, for all combinations of players. I would like to convert this into the probability of a player ...
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Comparing two groups based on how they ranked items

In a survey on Qualtrics, I have asked two groups (Group A and Group B) to rank their preferred mode of communication: "list the following modes of communication in order of your preference, drag ...
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What is a good metric for my item ordering/ranking task?

My dataset is a collection of items with numerical features, and each of them has a score assigned to it as label. My goal is to predict the ranking/order of the items, so the score prediction ...
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What is the proper way to rank machine learning models with multiple eval metrics?

What I'm doing now is ranking each model within each metric and summing the ranks. Whichever model has the lowest sum I am considering the best. Perhaps it would be clearer if I used an example There ...
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Kendall's Tau B Rank

Our study is about ranking 30 blue chip stocks in the Philippine Stock Exchange (PSE). We want to know the validity of a ranking method called The Technique for Order of Preference by Similarity to ...
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rank elements to minimize the median of the response at a certain rank

I have the following data. ...
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help with formula to calculate Bayesian ranking of M-star reviews

I wonder, if someone could help to understand a formula from a book please. Bayesian Methods for Hackers: Probabilistic Programming and Bayesian Inference (Addison-Wesley Data & Analytics) (...
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Compare two confidence intervals calculated from same sample

Problem: We have distance between user and a static device(in meters). We have lab tested data where user is actually standing away from device(actual values). Based on these we try to determine what ...
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How to use DecisionTreeClassifier on a problem involving ranks as features? [closed]

Let's say we have a dataset with these columns: A | B | C | D | E | F | G I want to predict [E,F,G] based on [A,B] with following rule: top 5 entries order by (SUM(D)/SUM(C)) desc Pseudo-SQL query ...
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How to incorporate score margins into the Weng-Lin ranking models?

I'm trying to figure out how to incorporate this formula from this paper into the Weng-Lin update rule algorithms: \begin{align} \mathcal{P}[i \text{ beats } j] &= \frac{\exp{\lambda_i}}{\exp{\...
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Measuring within-group similarity for ranked list responses

Individuals are completing a task in which they rank 15 items (1-15 according to importance). These individuals will later be working in groups of 4, so I am interested in measuring the similarity of ...
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Does non-zero Spearman rank correlation imply dependence of original variables?

Introduction Let say we have random variables $X$ and $Y$, and we take their rank transforms to be $g(X)$ and $g(Y)$. The Spearman rank correlation coeffiicient can be considered to be $$R[g(X),g(Y)] =...
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What are well-founded, off-line ranking algorithms for assymmetric games?

Consider the following setting: $n$ players (attackers) play an asymmetric, adversarial, 2-player game against $m$ other players (defenders). Two players may play each other $0$ to $k$ times, but each ...
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Outlier management

I apologize in advance for my novice question. I am a part of an interview committee of eight people. We interview 70 applicants for just six positions. All of the applicants are very accomplished. We ...
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What are the best ranking models availble?

I am looking to compare data for example with sports teams, compare recent and historical results. I want to be able to compare any two teams when needed and also take into account a players database ...
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(n)DCG without true relevance scores

I have a search engine that returns results with a normalized score on the scale 0.0 to 1.0. Higher score means higher relevancy to the input query. The ranked output scores look like this, e.g. [1.0, ...
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Comparing Star Ratings

Data Illustration NOTE: I do not have a stats background. I'm pretty sure I'll use some terminology incorrectly. I have come across several approaches via Python/SQL that I would like to confirm as ...
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How to approach ranking and explaining business driver independent variables?

I'm looking at quarterly sales for a fortune 500 company, sales being the dependent target variable. My independent variables include things like marketing spend, sales volume, and competitor market ...
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Ordering drug effectiveness from best to worst

Problem The (mean) effectiveness of a drug $d$ on trial $i$ is given by \begin{align} X_{di}:=\widehat{\mu}_{di} \sim \mathcal{N}(\mu_{di}, \sigma_{di}^2), \end{align} with known variances. Hence, for ...
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How to get point-wise scores in ranking with pairwise constraints

I am trying to solve a ranking problem with the following constraints: Input a set of items each of which is represented as a feature vector pairwise preferences between some pairs of items Output ...
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Evaluating ranking quality given ordinal values

I have a regression model which attempts to predict an F1-score given shared input features of a pair of models. I understand how to evaluate the quality of my regression model through using metrics ...
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Determining Frequency for Rankings based on their timeline

I have a dataset that reflects rankings for products over a long time period. I do not know how the ranking represents sales, but my first assumption is that I can apply Zipf's Law. However, I don't ...
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What's the problem with using Chi Squared to test association between likert / ordinal data?

I've seen that Chi Squared test won't take into consideration the ranking of ordinal data. I've not seen anything which outlines the risks / potential problems that could arise as a result of ignoring ...
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Ranking the Outputs of Statistical Models

I have the following question about Ranking the Outputs of Statistical Models. In the case of a regression model with a continuous response variable : Suppose the model makes predictions on 3 new ...
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Weighted imputation for ranking based on multiple variables

I need a suggestion for imputation of a data where there are missing values. yet I need to rank the items based on the data. Here's an example table to demonstrate this problem. There are 5 birds, ...
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Create a rank from multiple variables in SPSS

I am trying to create a rank from multiple variables in SPSS. I have a survey that has seven variables, measured on a 7-point Likert scale (from 1= not important to 7 = very important). For example, ...
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Search, rank and recommend in large text datasets

Imagine you are Spotify and you have billions of songs. Assume that each of these songs are transcribed into text. How do you design your search and recommendation pipeline such that when somebody ...
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Linear Regression - Data Subset with Lowest Mean-Squared Error?

Short version: given a linear regression dataset and an integer $K$, what data subset of size $K$ results in linear parameters with the lowest mean squared error on the entire dataset? Long version: ...
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How to get a meaningful loading while ranking by PCA with first component in R

I was thinking if there is a way to impose constraints on variables so that the loadings with first principal component takes values according the signs imposed to it in R. I have seen some of the ...
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Building a ranking model, using linear regression with manually updated inputs by end users

I am trying to solve a ranking problem and starting from a linear regression here. As a dependent variable I currently have the score of different authors in academic literature and want to convert ...
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