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Questions tagged [scoring]

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6 views

how to set the positive and the negative class for sequential features selection?

I'm working and classification problem, so after choosing Random Forest as a model, I should the best features for it, for that I used "Sequential Feature Selector" from ...
2
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0answers
55 views

Credit scoring using scorecardpy with XGBoost

I used XGBoost for scoring creditworthiness. At first I thought I could use predict_proba for scoring but then I saw that there was a module scorecardpy based on WOE to claculate code scoring. I tried ...
3
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2answers
41 views

Is there a definitive and more conclusive way of interpreting the R^2 score from a linear regression model in terms of prediction accuracy?

I'm trying to find a definitive way to conclude the R^2 score from a prediction accuracy point of view rather than variance. How should I do it? Conceptually, most blogs / articles explain R^2 as: ...
4
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1answer
82 views

Why is the F-measure preferred for classification tasks?

Why is the F-measure usually used for (supervised) classification tasks, whereas the G-measure (or Fowlkes–Mallows index) is generally used for (unsupervised) clustering tasks? The F-measure is the ...
3
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2answers
41 views

How can I compare classes from clusterings performed on two different data sets?

I have two data sets defined by real valued vectors, and I have performed clustering on both of them. Now I want to compare the classes to see how they map to each other. If I put the data sets ...
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0answers
54 views

Predict class having only class proportions for every attribute (non labeled data)

I am working with a big data set (millions of observations) where for each observation I am trying to predict a probability (or score it) of being of a class. I haven't any labeled training data and ...
0
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1answer
17 views

How to approach model reporting task

I have been tasked to report on an ensemble model that was created in h2o which includes several model subtypes such as Random Forest, GBM, linear models etc. The end goal is to predict churn rates ...
1
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1answer
20 views

Is the maximum BDeu Bayesian Network always the empty network?

I'm recently reading a paper about Scoring Mechanisms for Bayesian Networks. For the BDeu score, it appears that the maximum possible score of BDeu for Bayesian Network structure learning is zero. ...
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0answers
258 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 ...
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0answers
49 views

What is an appropriate way to compare classifiers with different sets of classes?

I have three classifiers for language identification: A: en, de, ru, fr, ij, kl B: en, de, ru, fr, xy C: en, de, ru, fr, no, pq, rs and I have a balanced dataset ...
2
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0answers
24 views

Intuitive interpretation of ratios between training set scores and validation set scores

I'm training models with the usual setup where you hold back a portion (in my case, 20%) of the data just to see how your trained model generalizes to unseen data, to see if it's overfitting. When ...
2
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3answers
78 views

How to learn to score new documents based on a existing set of scored documents?

I have a 50 000 documents of 1000 words or more ranked between 0 and 2000. They all deal with a similar topic. I'd like to create an algorithm that can learn to score new documents. What approach do ...
2
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1answer
636 views

Selecting the right algorithm for match probability prediction

Looking for assistance kick-starting a new machine learning scenario. In this case I need to pair one entity (ex. person) with a group of entities (ex. other people) given a history of matching ...
4
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2answers
1k views

Converting non-numeric data values into equivalent rank scores

Consider a data-frame similar to the one shown (the actual data-frame is much larger) ...
2
votes
1answer
695 views

Prediction model for marketing to prospective customers (using pandas)

I'm currently working on a part-time project which involves predicting the likelihood of customers going to buy a product using data analytics. The company I'm interning with has given me a customer ...
5
votes
2answers
820 views

Why are precision and recall used in the F1 score, rather than precision and NPV?

In binary classification problems it seems the F1 score is often used as a performance measure. As far as I've understood the idea is to find the best tradeoff between precision and recall. The ...
1
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2answers
134 views

Creating validation data for model comparison

I am working on building a scoring algorithm for student data, say the attributes are : name, location, age, class, school_name, skill1, skill2, skill3 based ...
4
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1answer
348 views

Comparing accuracy of models in ordinal regression / classification

I am looking into creating a model to predict whether an item is "Very Good", "Good", "Bad" or "Very Bad". After I fit the training data to the models, comparing the accuracy of the models during ...
2
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2answers
1k views

R in production

Many of us are very familiar with using R in reproducible, but very much targeted, ad-hoc analysis. Given that R is currently the best collection of cutting-edge scientific methods from world-class ...
2
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1answer
326 views

Rank players of any given sport

I've recently become interested in possibly of developing some sort of method for ranking athletes of sports such as American football and determining which players are better than others in terms of ...