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21 views

Proper scoring rules for observations with different supports

Suppose to have a bivariate variable $z_t=(x_t, y_t)$ indexed by $t=1,2, ..., T$. Suppose now that the two components have different support, i.e. in my specific problem $x_t \in \mathcal{S}$, where ...
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1answer
62 views

What data mining/machine learning approach to use for a scoring model?

Suppose I have a large data set with lots of features(attributes). And I'm tasked to build some kind of scoring model to rank certain objects with all these features. How do I go about doing this? ...
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0answers
9 views

Web page scoring function based on readability (LIX)

I'm creating a scoring system for web pages based on their level of readability using LIX. A selection of pages from a web site are crawled and given a score. Besides average and median, what ...
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2answers
197 views

Intelligence Squared Scoring and Winner Determination

There is an NPR podcast called Intelligence Squared. Each episode is a broadcasting of a live debate on some contentious statement such as "The 2nd amendment is no longer relevant" or "Affirmative ...
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1answer
35 views

Algorithm for scoring co-varying traits

I am sure this has been done, but I can't find quite the right approach. EDIT: Trying to explain better. The rows of colored boxes below are columns of molecular sequence data -- positions in a ...
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0answers
28 views

Relation between Scoring rule and Loss function in Parameter estimation and model selection?

Initially, I had only heard of MLE and use it for almost everything, e.g. point estimate and model selection (with some penalty). Then, MSE appeared, which seems to play the same role as MLE does. I ...
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0answers
32 views

Creating a model to interpret numerical scores

Good morning/afternoon everyone, first of all thanks to all of you for the valuable insights provided. I will be oulining here my current challenge, trying to provide as much detail as possible. ...
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0answers
19 views

Is there a reason to score on subsets of your data?

If you're training a model using cross validation on one set of data, and then you're scoring that model on a separate set of data, is it advised to score, say, 1000 times on subsets of your data? ...
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0answers
134 views

Random forest “certainty / likelihood score” - how to score records in RF mode in R?

My question is similar to this link Creating a "certainty score" from the votes in random forests? I am trying to build a random forest for a binary response (1 & 0). Let's say we have ...
0
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2answers
42 views

How to get an “averaged” score?

Assume a game wherein a character's "power" is made up of several factors, like speed, weight, body build, etc. And let's say that each of these factors were scored 0, 1, 2 wherein 0 means average, 1 ...
2
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1answer
132 views

Cluster many thousands observations (mixed variable types). Cluster subsample and then classify the rest observations?

I'm trying to run a cluster analysis on a large dataset (70k+ observations to cluster) with mixed variables (numeric, ordinal, binary and nominal). I don't think I can create the distance matrix using ...
3
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1answer
56 views

Deploying survival model for production

I've recently built a survival model with time-varying covariates (assuming equal time periods) using R and I am now in the process of putting this into Oracle for production using just the ...
1
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1answer
98 views

Scoring predictions of an ordinal variable

I read about using scoring rules to evaluate the performance of predictive models. In the Wikipedia article about the Brier score, it is stated: The Brier score is appropriate for binary and ...
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0answers
43 views

Correcting a DNA scoring algorithm for scanned sequence length (consensus binding site)

In this paper, the authors present a scoring algorithm for potential transcription factor binding sites, based on the position-specific probability matrix (PSPM) for that particular transcription ...
1
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1answer
786 views

Logistic regression: Fisher's scoring iterations do not match the selected iterations in glm

it happened to me that in a logistic regression in R with glm the Fisher scoring iterations in the output are less than the iterations selected with the argument ...
0
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0answers
46 views

How to score the options in a questionnaire and develop a scoring range in a risk profiler questionnaire?

I have developed a risk profiler questionnaire but don't know how to score the options and make a scoring range. Once the range is developed, I could categorize the client as conservative, moderate ...
2
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0answers
58 views

Creating an index that measures how accurate economsits are at predicting the US economy

I am interested in building an index that tracks how accurate economists are at predicting several US economic statistics: US Jobless claims number: comes out weekly, ranges from 100k to 400k, ...
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0answers
149 views

How to create a single rank / score number from a multiple set of variables that define the quality of something

I have several variables that describe the quality of a trading relationship between a client and financial institutions (FIs) the client deals with. The variables are populated with observed data ...
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2answers
259 views

Good books/papers on credit scoring

I'm looking for recomendations of books on credit scoring. I'm interested in all aspects of this problem, but mostly in: 1) Good features. How to build them? Which have been proved to be good? 2) ...
3
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1answer
153 views

Validation of a scale for a different population (CFA)

I'm currently adapting a coping questionnaire which has been widely used in sports to be used with a different population (musicians), so I need to address its reliability and validity with this new ...
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2answers
157 views

How can I estimate a “confidence” in a score / rating

I'm sure there's a more technical term for what I'm looking for, but I don't know what it is (it's not confidence intervals, I think) I'm trying to make a system where people get ratings (from 1 to 5 ...
5
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1answer
176 views

How can I devise a scoring system for a competition that is more fair than straight percentages?

I am trying to come up with a method for deciding the winner from among eight student groups competing for a prize. The raw data and corresponding percentages measure participation per group in a ...
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2answers
271 views

Comparing player percentages effectiveness with different sample sizes

I have a spreadsheet of player data. One of the categories of player data is pass percentage. Pass percentage is calculated as follows: AccuratePasses/TotalPasses ...
2
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1answer
143 views

Determining conserved features using a Bayesian approach

I would like to perform some sort of binary classification, and my data set consists of 100 examples (for each class), which are vectors with 2500 elements. Ideally, I would like to determine which ...
0
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0answers
470 views

What helps (justification) to decide cut score/cutoff points for 5-point likert scale?

I am wondering what are the factors involved in deciding the cutoff value / cut score for 5-point likert scale from: ...
1
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1answer
245 views

Confidence interval scoring

Question migrated form http://stackoverflow.com/questions/10019576/confidence-interval-scoring-with-programming-languages#comment12812602_10019576 I used a CI scoring algorithm from ...
2
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2answers
154 views

Detecting patterns of cheating and collusion in competition

I'm looking for ideas on how to discover cheating in sports that have judges awarding points. I can't name the sport since I participate in it at the moment. It's been known for a long time that this ...
2
votes
1answer
190 views

Scoring new observations after cross-validation

I have some doubts about cross validation and scoring a new set of observations. Let's say I want to predict $y=b_0 + b_1x_1$ and have built a 10-fold cross-validation data set, run a regression ...
1
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1answer
169 views

What is the rationale for using scoring methods after logistic regression?

I generally come across scoring in logistic modeling (also other methods like discriminant analysis, etc.). I want to know what is the use of scoring of individuals after running a logistic ...
2
votes
1answer
69 views

Re-estimate classification model with biased data

Let's say that I score (with, for example, a logit model) a group of 10,000 customers according to their potential of buying a product, and that I decide to contact the top 1,000 with a special offer. ...
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0answers
205 views

How to combine unbound variables with very different frequency distributions?

I want to combine three unbound variables. Each variable is the score provided by three different algorithms. Each algorithm predicts the likelihood (score) that a specific interaction between two ...
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0answers
117 views

How to combine three different scores

I have a population of 300 cases. It's split in three sub-populations 50, 50 and 200 in size. I have developed three (different) models resulting in a score variable which rank orders each of the ...