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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8 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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11 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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19 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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22 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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12 views

Creating Scoring Functions

As a data scientist/analyst is there any resource I can use to solve non-conventional supervised/unsupervised learning problems, for example: Based on hotels in a city create a score for how popular ...
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9 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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13 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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31 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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12 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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18 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
20 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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19 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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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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41 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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18 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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187 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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24 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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30 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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27 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
19 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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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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89 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
57 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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42 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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45 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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40 views

nDCG - choose relevance scores

I am evaluating a recommender system using nDCG. The recommender system predicts similar movies for a given movie. I want to evaluate predicted similarity rankings by comparing them to a ground truth ...
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7 views

Alternative ranking evaluation metrics for biased data

What are some alternative evaluation metrics for ranking problems, that could help when evaluation is done on heavily biased data? Example - if we sort items by their price and want to evaluate ...
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10 views

Will re-ranking my results slow down my search?

I'm looking into incorporating ranking in my website by using a machine learning model. But to rank my documents I have to calculate all my features (like tf-idf, word count, etc..) on every document ...
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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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12 views

How to normalize old accumulated ratings

I am playing around with data-set which contains movies and their ratings by various users. I am trying to rank these movies based on their user ratings. However, as obvious, many of the old movies (...
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36 views

Rank by sorting the output probabilities of a binary classifier or by “learning to rank”?

I have a binary classification problem (5M points, only around 0.01% is positive). As output I want to give a list of data points sorted by "positiveness", and then only the top ...
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1answer
137 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
54 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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19 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
209 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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97 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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403 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 ...
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1answer
99 views

What is the difference between nDCG and rank correlation methods?

When do we use one or the other? My use case: I want to evaluate a linear space to see how good retrieval results are. I have a set of data X (m x n) and some weights W (m x 1). I want to measure ...
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77 views

Feature selection with information gain (KL divergence) and mutual information yields different results

I'm comparing different techniques for feature selection / feature ranking. Two of the techniques under scrutiny are the mutual information (MI) and the information gain (IG) as used in decision trees,...
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105 views

Constructing a graph where any node can have the highest PageRank among all nodes

I'm trying to solve q5.1.4 in mmds chapter5, however, I'm not sure how I can even start. The question is: Construct, for any integer n, a Web such that, depending on β, any of the n nodes can have ...
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1answer
74 views

Multilabel Classification With Ranking

I have a dataset as below: ...
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1answer
34 views

Best way to narrow down a list and rank based on attributes?

I have a mortgage/credit data set that contains a list of customers (600k rows) and has a 100 columns inclusive of the customer's general info (address, city, zipcode, etc), income, fico scores, ...
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15 views

Predicting sequences newbie question [closed]

I have a ranked list of rows of 100 lines of data 1- 8 4 0 5 9 3 2- 0 3 3 5 3 2 3- 0 0 2 4 0 2 .. 100- 0 2 3 2 2 0 Is it possible to predict a) when given a new ...
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211 views

NDCG score is greater than 1

I'm solving a problem of ranking classes for each unique id based on the utilization quantity. I have 6 unique classes in the training and test data. My neural net mode predicts the utilization ...
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31 views

Reduce number of vectors in dataset to achieve the “same average dimensions result”?

I have many tests (rows), each with a large set of 3D vectors (features/cols). Each vector complies: Xn + Yn + Zn = 1 Simply averaging all components ...
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1answer
194 views

Two definitions of DCG measure

I wanted to check the definition of Discounted Cumulative Gain (DCG) measure in the original paper Jarvelin and it seems it differs from the one given in the later literature Wang. Originally, for $n$ ...
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108 views

Statistical Significance in Pairwise Ranking Algorithm

Can anyone recommend an algorithm/toolkit to rank items that have been rated in a hot-or-not style that gives statistical significance? For example, out of a set of N images, two images are shown to ...
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189 views

Statistical Significance for Pairwise Ranking Algorithm

I am using this library: https://github.com/lucasmaystre/choix/blob/master/notebooks/intro-pairwise.ipynb to rank items that have been rated in a hot-or-not style. For example, two images are shown ...
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1answer
74 views

Sparse IR with user feedback

I'm considering a problem framing within an information retrieval context. I have a sequence of documents that feature different attributes. In the web context, these would be webpages. One ...