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.

Filter by
Sorted by
Tagged with
2
votes
0answers
10 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 ),...
1
vote
2answers
53 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 ...
1
vote
0answers
49 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, ...
1
vote
0answers
18 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....
4
votes
1answer
34 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 ...
2
votes
1answer
36 views

How to extract keywords from a list of URLs?

I have a bunch of URLs in a text file like- ...
0
votes
0answers
23 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 ...
0
votes
0answers
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 ...
0
votes
0answers
8 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 ...
1
vote
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, ...
0
votes
0answers
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 (...
0
votes
0answers
26 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 ...
0
votes
1answer
46 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 ...
0
votes
0answers
15 views

Any there databases with native support for applying a NN model to produce search rankings?

The Situation: I have a simple neural net with an input vector that consists of the euclidean distance between the attributes of two cars. (For example the attributes would include wheel size, car ...
0
votes
0answers
13 views

How to adjust ranking function

I have a ranking function that ranks particular markets in a way where their features are highly desirable. However, I can look at the results of the rank and see that it's good, but how can I make it ...
0
votes
0answers
20 views

PageRank computation with dumping (scaling) factor

it is not clear to me how to calculate two iterations of PageRank computation on the following network with dumping (scaling) factor s = 1.how can they calculate it correctly?
2
votes
2answers
47 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 ...
1
vote
0answers
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 ...
2
votes
1answer
204 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 ...
1
vote
0answers
77 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) ...
1
vote
0answers
305 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 ...
2
votes
1answer
63 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 ...
1
vote
0answers
61 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,...
0
votes
0answers
19 views

Item item similarity from both user data and content

I'm creating an item-item similarity matrix by combining implicit user data and static content data of the items. How can I determine the weights for these two data and the weights for different ...
1
vote
0answers
69 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 ...
1
vote
1answer
69 views

Multilabel Classification With Ranking

I have a dataset as below: ...
0
votes
1answer
29 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, ...
0
votes
1answer
14 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 ...
1
vote
0answers
151 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 ...
2
votes
0answers
28 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 ...
2
votes
1answer
175 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 $n$ ...
1
vote
0answers
93 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 ...
1
vote
0answers
170 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 ...
3
votes
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 ...
3
votes
2answers
108 views

Learning to Rank Application

If there's a website/app that sells products and my job is to determine the order/ranking in which the products should be displayed. For example : I click on restaurants and a list of restaurants ...
1
vote
0answers
14 views

business ranking based on transaction data

I have some customer (say 10,000 customers) transaction data of many stores, what would be a good approach to rank these stores? The transaction data is of entire year, and the transaction data ...
3
votes
1answer
129 views

Methods for ensembling ranked lists?

I was wondering if there's a good way to use ensembling when I have two or more algoritims producing ranked lists. That is, suppose I have the following datasets consisting of ordered lists (higher ...
4
votes
1answer
581 views

Can feature importance change a lot between models?

I have a random forest classifier and Multinomial Naive Bayes. For feature importance, I used gini index for random forest and for Multinomial Naive Bayes I used the coefficients of each feature. Then ...
2
votes
1answer
101 views

Peformance evaluation of ranking algorithms

I have three questions: How can we assess (or measure) the performance of the ranking algorithms? Are there any specific measures, or performance metrics, for this? More specifically, how can we ...
1
vote
2answers
881 views

XGBoost ranking file format

The xgboost package has two files that must be used for ranking: train.txt with the data ...
1
vote
1answer
3k views

Cosine similarity between query and document confusion

I am going through the Manning book for Information retrieval. Currently I am at the part about cosine similarity. One thing is not clear for me. Let's say that I have the tf idf vectors for the ...
1
vote
0answers
92 views

Information measure of rank changes?

I'm trying to compute the information content of a function that reranks a list. Perhaps more precisely, I'm trying to compare the information content of different arguments to that function. ...
0
votes
1answer
69 views

Model with rank as the dependent variable?

I have a dataset with n records. The input features are f1, f2, f3 ... fm, and the dependent variable (output) is just the rank (not any type of scores). What type of model should I build so that I ...
1
vote
1answer
132 views

Learning to rank: construct absolute ranking using pair-wise ranking approach

I am learning about the "pairwise approach" for learning to rank. As far as I understood, the training output is a partial ranking function $r$ that: given given some query $q$ and two document $d_i$ ...
2
votes
0answers
373 views

Ranking algorithm based on a handful of features

I am trying to determine the apt algorithm for a ranking problem that I am working on. I have social media metrics - engagement, sentiment, audience size etc for several brands and am looking for a ...
1
vote
0answers
396 views

xgboost - How do I treat document ID in pairwise ranking

I am trying to use xgboost in R for pairwise ranking for an implicit dataset. For simplicity, let's assume that I am dealing with a search problem, where I want to rank documents relative to a given ...
1
vote
1answer
46 views

Rating the Models

I am working with Multi variate time series Analysis using different Models in R. I used Arima, glm, ...
2
votes
0answers
334 views

Learning ranking

This is a sort of a follow-up to this newbie question:Suppose I want learn ranking (so, I have a bunch of data points, ranked $1, 2, 3, ...$ Now, one way is to use something like logistic regression ...
1
vote
1answer
62 views

Learning comparisons

Suppose I want (the machine) to learn the ">" function, and my training set is a collection of pairs of numbers $(n_1, n_2)$ with the output True if $n_1 > n_2$ ...
5
votes
4answers
6k views

From pairwise comparisons to ranking - python

I have to solve a ranking ML issue. To start with, I have successfully applied the pointwise ranking approach. Now, I'm playing around with pairwise ranking algorithms. I've created the pairwise ...