Questions tagged [predictive-modeling]

Statistical techniques used for predicting outcomes.

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58 views

What techniques are used to understand call patterns?

I have customer data since 2013 and there is a file which has the customer unique id, a timestamp, and the reason for the call (a drop down from the person who handled the call). I did some ...
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1answer
1k views

Analyzing survey data for predictions

I've got survey data that resembles: ...
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1answer
70 views

Predicting earthquakes using disturbances in DTH TV transmission

It is said that before an earthquake happens, a viewer experiences disturbances in DTH TV transmission in the form of distorted images on the screen which automatically correct after a few seconds. ...
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2answers
569 views

Using clustering and Lasso with cv

I used clustering on my dataset. Now when I'm trying to use a LASSO with cv to predict a response, one of the variables it takes into consideration is which cluster a new point is classified into.(I ...
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1answer
42 views

What algorithmic approach for selecting similar, relevancy based documents

I have an application that tracks people making mentions of various topics. We've used a Bayes algorithm to do some simple classification (users give a thumbs up/thumbs down) to pick the people that ...
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1answer
906 views

Predictive Model for Customer Payment Pattern

I am working for a logistics firm and there are approx. 750+ customers who avail our services. I am in the process of building and generating some insight for the business based on the payments made ...
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1answer
516 views

Best way to format data for supervised machine learning ranking predictions

I'm fairly new to machine learning, but I'm doing my best to learn as much as possible. I am curious about how predicting athlete performance (runners in particular) in a race of a specific starting ...
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1answer
3k views

Forecasting sales and creating model [closed]

In a assignment we are given macro economic indicators like GDP, Consumer price index, Producer Price index and Industrial production index. Also we are given Crude oil, Sugar prices and FM-CG Sales. ...
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3answers
1k views

Predicting Soccer: guessing which matches a model will predict correctly

I took on a project to predict the outcome of soccer matches but it turned out to be a very challenging task. I tried out different models but I only got 50-54% accuracy on my test dataset. Some of ...
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1answer
551 views

Combining data sets without using row.name

I start with a data.frame (or a data_frame) containing my dependent Y variable for analysis, my independent X variables, and some "Z" variables -- extra columns that I don't need for my modeling ...
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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 ...
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1answer
265 views

Interested in Mathematical Statistics… where to start from?

I have been working in the last years with statistics and have gone pretty deep in programming with R. I have however always felt that I wasn't completely grasping what I was doing, still ...
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1answer
123 views

problem of choosing right statistical method for scheduler prediction

I am struggling to choose a right data prediction method for the following problem. Essentially I am trying to model a scheduler operation, trying to predict its scheduling without knowing the ...
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2answers
631 views

How to start the process of coming up with the predicted math score?

I am working on a problem(non competition) from hacker rank https://www.hackerrank.com/challenges/predict-missing-grade Basically you're given test data of a bunch of students of their scores in ...
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3answers
696 views

machine learning on athlete performances to predict the time in a future race

Example Data I have a dataset (in R as a data frame) of race results for athletes. ...
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4answers
201 views

Format of CSV file

I'am trying to create a regression based prediction (like booking website): predict the number of clicks for each hotel. I have to generate a .csv file containing two columns: ...
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1answer
641 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 ...
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2answers
150 views

Could someone please offer me some guidance on some kind of particular, SPECIFIC project that I could attemp, to “get my feet wet, so to speak” [closed]

I am COMPLETELY new to the field of Data Science, mainly because every employer I have worked for, simply COULDN'T sell any customers anything that would use techniques learned in this field. Of ...
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1answer
215 views

Which Graph Properties are Useful for Predictive Analytics?

Let's assume I'm building a content recommendation engine for online content. I have web log data which I can import into a graph, containing a user ID, the page they viewed, and a timestamp for when ...
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2answers
166 views

Time series: variations as a feature

I am trying to predict clients comportement from market rates. The value of the products depends on the actual rate but this is not enough. The comportement of the client also depends on their ...
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1answer
1k views

predict with Multinomial Logistic Regression

If I execute the following code I have no problem: ...
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1answer
129 views

Web Framework Built for Recommendations

I'm wondering if there is a web framework well suited for placing recommendations on content. In most cases, a data scientist goes through after the fact and builds (or uses) a completely different ...
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0answers
81 views

Decision trees, categorizacion and oversampling

I want to create a model to predict the propensity to buy a certain product. As my proportion of 1's is very low, I decided to apply oversampling (to get a 10% of 1's and a 90% of 0's). Now, I want to ...
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0answers
84 views

Cross-sell models and additional holders

I would like to pose a question about how to treat additional holders in the propensity-to-buy models of banking products. Up to now I was only taking into considerations the clients as first holders....
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3answers
1k views

What regression to use to calculate the result of election in a multiparty system?

I want to make a prediction for the result of the parliamentary elections. My output will be the % each party receives. There is more than 2 parties so logistic regression is not a viable option. I ...
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1answer
59 views

Smoothing Proportions :: Massive User Database

What are some possible techniques for smoothing proportions across very large categories, in order to take into account the sample size? The application of interest here is to use the proportions as ...
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5answers
511 views

Can Machine Learning be applied in software developement [closed]

I'm from programming background. I'm now learning Analytics. I'm learning concepts from basic statistics to model building like linear regression, logistic regression, time-series analysis, etc., As ...
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3answers
5k views

Relationship between KS, AUROC, and Gini

Common model validation statistics like the Kolmogorov–Smirnov test (KS), AUROC, and Gini coefficient are all functionally related. However, my question has to do with proving how these are all ...
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1answer
205 views

Modeling when the response variable has too many 0's and few continuous values?

For problems where the data represents online fraud or insurance (where each row represents a transaction), it is typical for the response variable to denote the value of fraud committed in dollars. ...
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3answers
320 views

Differences in scoring from PMML model on different platforms

I've built a toy Random Forest model in R (using the German Credit dataset from the caret ...
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2answers
323 views

Regression Model for explained model(Details inside)

I am kind of a newbie on machine learning and I would like to ask some questions based on a problem I have . Let's say I have x y z as variable and I have values of these variables as time progresses ...
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1answer
5k views

Hashing Trick - what actually happens

When ML algorithms, e.g. Vowpal Wabbit or some of the factorization machines winning click through rate competitions (Kaggle), mention that features are 'hashed', what does that actually mean for the ...
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2answers
6k views

Looking for a strong Phd Topic in Predictive Analytics in the context of Big Data

I'm going to start a Computer Science phd this year and for that I need a research topic. I am interested in Predictive Analytics in the context of Big Data. I am interested by the area of Education (...
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1answer
3k views

Predictive modeling based on RFM scoring indicators

RFM - is a ranking model when all customers are ranked according to their purchasing F requency, R recency and M monetary value. This indicator is highly used by marketing departments of various ...
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8answers
12k views

Why Is Overfitting Bad in Machine Learning?

Logic often states that by overfitting a model, its capacity to generalize is limited, though this might only mean that overfitting stops a model from improving after a certain complexity. Does ...

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