Questions tagged [ranking]

Ranking is ordering data from highest to lowest or *vice versa.* For questions about *constructing* scores to use in ranking, please use the "valuation" tag, too.

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22 views

Changing behaviour of an ML model

I am trying to create a ranking system for recommending books to an user. Let's suppose we have some subjects of books like 'A', 'B', 'C', 'D' and from the past behaviour, it is observed that the user ...
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42 views

precision@k and recall@k

Normally, I am familiar with precision and recall evaluation metrics but as you know recall@k and precision@k are different things and used in ranking evaluations especially recommendation systems. I ...
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15 views

MongoDB Groupby Rank [closed]

Im Working With Mongodb And Wanted to do a query using Aggregate fucntion. Query Is ...
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25 views

Find top features that determine movie rank

I am trying to analyze a movie dataset in order to find the specific features which determine whether or not the movie is in the top-10 movies of the year (or likewise the worst-10 movies of the year)....
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21 views

ANOVA Feature Scoring

in order to score features, in ORANGE, using ANOVA scoring, the features should have a normal distribution? Thank you, J
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22 views

The upper range of a collected dataset is most likely accurate, but the rest may suffer biased omissions: How to call this phenomenon?

Background: In collecting a dataset of a specific unit ordered by a numeric variable, it is possible that the upper 'cloud' of the dataset is correct, while the 'tail' seems inaccurate. I can thus ...
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23 views

paired t-test shows no difference between median and Wilcoxon test p value shows that there is a difference between median values ? How to interpret?

I have a dataset. I wanted to do paired t test on it. So I carried out normality test and it showed that it does not follow normal distribution. So I used Wilcoxon test in place of paired t test. The ...
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34 views

Weighting of features in Recommender Systems

I'm new to Recommender Systems, and wanted to figure some things out in order to make the best possible Content Ranking System. I want to make a ranking of all the content (and content providers) ...
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1answer
29 views

Is there a good alternative to XGBoost for learn to rank?

My problem with XGBoost is that when I load the train dataset into the XGBoost DMatrix, there is a memory spike that is unavoidable, and I can't get my dataset loaded into RAM without crashing first. ...
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25 views

Ranking metrics: weighted and different

I have 2 ranking lists and I want to see how similar are they between them. setA = {10,9,8 ,7 ,6,5,4,3,2,1} setB = {4,5,12,14,9,8,7,6,2,1} There are the following constraints: 1. High number (or if ...
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1answer
21 views

Ranking of feature sets which will be used for binary classification

I have some feature sets say X1 and X2 ... Each feature set have some variable amount of features and there is no intersection between different feature sets Say X1 have 100 features and X2 have 500 ...
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1answer
45 views

Cosine Similarity but with weighting for vector indexes

I am very new to NLP and although this seems like a basic question I don't know how to search for an answer online. This is my problem: I have extracted and ranked keywords from 2 text sources: A ...
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53 views

Ranking problem and imbalanced dataset

I know about the problems that imbalanced dataset will cause when we are working on classification problems. And I know the solution for that including undersampling and oversampling. I have to work ...
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15 views

What does “freedom” mean in the RankNet paper?

In the RankNet (Learning to Rank using Gradient Descent) paper, paragraph 3.1, it said given the consistency requirements, how much freedom is there to choose the pairwise probabilities? What does ...
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1answer
51 views

What can help decrease outliers' influence on non-tree models?

I have a feature with all the values between 0 and 1 except few outliers larger than 1. I am trying to collect all the methods that can help to decrease outliers' influence on non-tree models: ...
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28 views

Standardizing binary decision with other scales (Like 1-5)

In the company I work for there are 2 different evaluation metrics for a song: Yes / No (Equivalent to like/dislike) 1-5 Scale Customers can use both to rank songs they like. I would like to create ...
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9 views

Visual/intuitive comparisons between various pairwise loss functions for learning-to-rank tasks

In learning-to-rank, There are various pairwise loss functions such as Bayesian Personalised Ranking (BPR) or Weighted Approximate-Rank Pairwise (WARP), etc. I know that these aim at different ...
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1answer
24 views

What is the best way to pick the optimized configuration from this dataset?

I have about 8000 configurations in an excel sheet. each configuration has four scores as seen in the image below. I would like to choose the best solution that has the highest lighting level score, ...
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17 views

How to use the position factor in known data as a feature in recommendation surfacing?

The problem is recommending stories on a website, just below each story based on how similar the stories are and some historic data based on what recommended stories were clicked or not clicked. So ...
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1answer
16 views

Dataset recommendation, ordinal target variable

Does anyone have any recommendations for datasets with an ordinal target? I'm currently using a rounded target from the Boston dataset. ...
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1answer
70 views

Using BM25 to rank words

How effective is it to use BM25 to rank words, to be more specific i have a dictionary of words and i want to rank only words in a document that are also in my dictionary. I want to rank all words in ...
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1answer
25 views

How to adjust/smooth a certain number using constants or rules

Hi, I am handling a dataset with a customer purchase history. The field ord_cnt represents the purchase without coupon usage, and cpn_ord_cnt represents the purchase with coupon usage. There are two ...
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37 views

TF-Ranking transform data to ELWC - ExampleListWithContext

I have read all the guides, videos, and everything, but I have no idea how to convert my feature set to an ELWC datasheet format for TF-Rank ListWise problem. There is no description of this structure....
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18 views

Recommended papers on Deep Ordinal Regression?

Can people please recommend papers on Deep Ordinal Regression? I'm looking for both the basic papers and the current important state-of-the-art ones - basically, everything that one "must" know in ...
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46 views

How to explain a stable NDCG@K in extreme multilabel recommender model

I am working in a multilabel recommender project and I try to evaluate it as a ranking problem. I calculate recall@k and precision@k which both looks quite well. Recall increases and Precision ...
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28 views

Ranking aggregation - How to select the “best” item out of multiple rankings?

For the sake of example, let's say that I am interested in selecting the "best team of all time" based on league standings from the last 30 years. Let's assume that I have $T$ teams, and each year, ...
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47 views

English Word popularity scoring

I'm new to data science and looking for the word popularity ranking algorithm. Given a list of words, What would the best and easy to implement algorithm to score each word based on the word ...
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1answer
24 views

Analytic Hierarchy Process - consistency ratio over 50%

I have such data of pair-wise comparison. I calculated consistency ratio for this data of 56%. That's too high for relevant results. Whether is possible to modify initial data to improve consistency ...
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1answer
26 views

Compare ratings of players over different leagues

I want to compare ratings of players from different leagues and predict rating of player in a league he/she didnt participate in. Rating of a player is estimated within a league where he was playing. ...
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12 views

Solving Feature Distribution variance between Training and Prediction for Ranking models

I am building a linear regression model to improve ranking of documents. And trying to identify problems due to which model performance estimates don't match actual impact One major problem is ...
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2answers
1k views

Preparing for a Machine Learning Design Interview

I am not sure if this is a relevant post here but: I made it to the final round for the Machine Learing Engineer position at Facebook. The final round interview is virtual (thanks to Corona) and will ...
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1answer
31 views

Drastic drop in Somers' D ? Why?

I came across to find the correlation between the ratings assigned by two coaches to a same group of 40 players. I have tabulated the results as below: The Somers' D is 50%. However, for the case ...
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614 views

What is query id (“qid”) in XGBoost

In XGBoost documentation it's said that for ranking applications we can specify query group ID's qid in the training dataset as in the following snippet: ...
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1answer
34 views

What are some significance tests to rank features(multiple) before training the data

I have 8 features for a classification problem. The target value tells if there was an anomaly or not. I want to run some significance tests to rank each feature, as being a distinctive feature of ...
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1answer
133 views

Differentiable loss function for ranking problem in regression model

In regression problem, we may need a loss function to measure the relative ranking accuracy between targets $y$ and predicted values $y_{pred}$. Abviously, the simple MSE does not consider such ...
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1answer
33 views

what metrics to evaluate rank order results?

I have searched on stackexchange and found a couple of topics like this and this but they are not quite relevant to my problem (or at least I don't know how to make them relevant to my problem). ...
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1answer
27 views

Recommender system that matches similar customers with similar highly rated products?

I have a dataset of 1,000 customers that bought 20 distinct phones and rated them 1-5. I have several demographic attributes for these customers (gender, age). My website offers 100 distinct devices, ...
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1answer
402 views

How to use ndcg metric for binary relevance

I am working on a ranking problem to predict the right single document based on the user query and use the NDCG metric to measure the model. Given the details : Queries ( Q ), Result Document ( D ),...
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2answers
133 views

How to calculate precision at K and NDCG for ranking algorithms

I am ranking a filtered item list as per user's metadata and historical behaviour. Now how to calculate metrices like precision at K? One approach could be - Divide historical data in training and ...
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1answer
80 views

Is it Possible to Use Machine Learning for Ranking Alternatives?

Right now, I’m working on road and street safety analysis. I have a dataset of dangerous points in four regions of a city. Some of the available variables are road lighting status, ITS, latitude, ...
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21 views

Calculate a Rank function from Regression features

I am using 3 features (x1, x2, x3) for regression. Some of my features are continuous some are categorical. My dependent variable are lets number of bookings. And I can predict the number of bookings....
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1answer
50 views

How is “relevance” defined in information retrieval outside the context of systems with user feedback?

I've seen information retrieval systems that return some results from a query, and then the user rates these results as either "relevant" or "not relevant". What can you do if you do not have user ...
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1answer
333 views

How to extract keywords from a list of URLs?

I have a bunch of URLs in a text file like- ...
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0answers
24 views

Alternative for ranking of a response

Is there a regression approach for predicting the rankings (ordering) as an endogenous variable? I would like to fit a regression to a dataset where the response is the order of a variable: 1st, 2nd, ...
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1answer
535 views

Compare Rows Within a Group and Rank Best to Worst

I'm interested in an approach for comparing rows "within group" to produce a ranking from best to worst based on the performance relative to other rows within a group. For example, if given this ...
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2answers
82 views

Calculate a ranking function from classification features

I am using 3 features (x1, x2, x3) for binary classification. All my feature values are in 0 to 1 range (unit range). I obtained how important each feature was in ...
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20 views

Personalised search ranking for hotels

I've built hotel embeddings which gives very satisfactory results in returning similar hotels for each hotel. Now the problem I'm trying to solve is to rank the hotels in order of relevancy to the ...
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1answer
227 views

Improve results using user input

I've developed a tool that retrieve the closest expressions from a database based on what the user typed. (using word embedding - a comparison is made between each expression from the database and the ...
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138 views

What does the ratio of precision/recall to their ideal values mean, and why are they equal?

When evaluating rankings, Normalized Discounted Cumulative Gain (NDCG) normalizes the score to a [0,1] range by dividing by the ideal score. What happens if we take the same idea to Precision (Pre) ...
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505 views

Xgboost rank:ndcg learning per group or for all dataset

I'm trying to implement xgboost with an objective of rank:ndcg I want the target to be between 0-3. In my data for most of the groups, there is only 1 event per ...