# Tagged Questions

Predictive models are statistical models whose primary purpose is to predict other observations of a system optimally, as opposed to models whose purpose is to test a particular hypothesis or explain a phenomenon mechanistically. As such, predictive models place less emphasis on interpretability and ...

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### Projecting the lifetime value of a subscription customer

We are looking for a way to predict the lifetime value of a subscription customer for a new subscription based company. The problem is that we won't know what the lifetime value of a customer is until ...
9 views

### Simulate future values from a multilevel model

I have data set of short series with a multilevel structure, where I suspect the lag might be a good predictor. I want to simulate future values based on the model. I am not entirely sure I am going ...
61 views

### Best way to visualize predictions from a linear model

Let's say I'm doing some predictive analytics and am trying to predict US GDP per month using a two or three month lag. After every month, I generate new predictions and am able to compare my ...
79 views

### Best method of calculating line of best fit / extrapolate to compensate for delays

Let's suppose there is a project which is expected to take a certain amount of time to complete. As certain jobs are done, we can quantifiably measure how much of the project has been completed at any ...
11 views

### “Predicting” future usage based upon previous usage

As a neophyte in statistics, I've got a question and a very long plane ride to try to work on the problem / read. I've got n~100000 customers who make phone calls through my service. They all have ...
39 views

### Comparing linear regression models created from different data sets

I have one linear regression model [Mold] created from 12 points where I can calculate a single value of RMSE between the predicted values and the actual observed values. This model is then used to ...
44 views

### How can I find out how shifts in a country's fiscal policies affect its economic health?

I have the values of certain variables for 20 years for different countries... I am unable to understand how to use the values of a particular variable for 20 years. Could anyone suggest how I should ...
80 views

### What are the most commonly used predictive models when dealing with binary data?

I know everybody uses logistic regression as the starting point, but I'm curious to know: What are the other commonly used predictive models when data is primarily binary?
22 views

### Zero inflate models vs generalized mixture model

Hi I am looking to compare the fit of a zero- inflated mixture model and a poisson mixture model, the random effects in both models are different. Comparing the fitted values of both models ignores ...
26 views

### What's the name of this quantile curve estimation technique?

I'm still working with the same dataset as in a previous question here. Quantile regression has taken me some way, and now I'm going further. The underlying relationship between these x and y ...
54 views

### Interpretation of regression data, RMSE, and model predictions

I am doing an analysis where I am using one data set of 12 rows (Mold), and running a linear regression analysis on this data set to generate two different linear regression equations. From there I ...
75 views

### Auto-Regressional & Moving Average Model Formula Properties

I seeking help in understanding specific values underlying the formula's for the MA(p) model & the AR(q) model. I am attempting to implement the models (building up to the combined ARIMA model) in ...
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### Machine Learning techniques for classifying response from several continuous factors

I have some data with rows corresponding to male-female pairs, with 8-10 continuous factors (that have been unfortunately anonymized) that apply to both the male and female, and whether they became ...
68 views

### Methods / approach to improve the predictive accuracy of a logistic regression model

The situation: I have a logistic model that should predict a defect (1=defect, 0=no defect). My model uses 4 out of 14 parameters, which are significant for my ...
126 views

### Prediction evaluation metric for panel/longitudinal data

I would like to evaluate several different models that provide predictions of behavior at a monthly level. The data is balanced, and $n=$100,000 and $T=$12. The outcome is attending a concert in a ...
54 views

### Learning curve shows decreasing accuracy

I'm working on a random forest classifier with 10-folds CV to aestimate the hyperparameter 'mtry' (chosen by maximizing AUROC). I decided to pre-split the training set in 8 samples equals in size ...
33 views

### Comparing probabilities of two different models - apples to oranges

I have 5 logistic models for 5 products. For recommending a product to a customer, I want to rank order the products by their probability scores. The problem arises because I am comparing apples to ...
50 views

### Is it always bad to retrain your model to include predicted data?

I understand intuitively why this is a horrible idea - you assume your model is correct and then increase your number of observations which will likely result in a poor fit on future data. I'm ...
160 views

### What machine learning techniques can, once trained, generate prediction despite some missing inputs?

I have a training set where the inputs & outputs are all present, but I suspect that in the data where I want to do prediction, I will occasionally encounter scenarios where a small fraction of ...
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### Assessing whether 2 models differ “substantially” (though equal RMSE), to improve prediction

In preparation of stacking several models, I would like to gather some heterogeneous models. I am not sure, but expect that the stacking will improve when I have very different models, though all have ...
172 views

### Time series factor model with one series more frequent

Let's say I have two time series, one of which updates more frequently than the other: $x_0,x_1,x_2,\dots,x_t,\dots$ $y_0,y_{10},y_{20},\dots,y_{10t},\dots$ I want to fit a model to this that ...
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### C5.0, boosting, and mislabeled data

I'm trying to model a binary classification problem. 5 continuous features, slightly imbalanced dataset (about 60 in one class, a little more than 200 in another). So far I've tried kNN, LDA, and ...
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### How to deal with data having huge disparity in number in each class

I have data in which the number of negative cases in response is approximately 98% of the total sample size (total # records are approximately 1 million, Response is ...
153 views

### Creating an estimator with varying shock levels (SD) in R?

First time posting! I'm trying to create a logit estimator using a looping simulation, where the loop detects the number of correct prediction (my code is below). Is it possible to change the shock ...
26 views

### A multi-label classification for tagging short text

I am fairly new in the area of text mining and want to practice my skills a little. I have the following task at hand which I want to work on. I have a large list of short texts (~100.000) and every ...
23 views

### Building a predictive index based on 3 independent variables

I have 3 variables containing 1 TO 5 vote as key performance indicator (kpi) responses to a client survey. Using RapidMiner and logistic regression I noticed that they are mildly predictive of a ...
55 views

### How to predict demand from historical “continuous” event data (date, lat, lon)?

I am attempting to predict demand for our service, both quantity but maybe more important, location (hotspots). I am by no means an experienced statistician, so I need some help :) I have all the ...
183 views

### Incorporating a treatment into a classification scheme

I have about 400 pieces of silver of different geometric dimensions. They were assigned to six groups and each group went through a series of stress tests, such as bending, pulling, putting in fire ...
456 views

### How can I generate predictions from the randomSurvivalForest package in R?

I'm trying to use the randomSurvivalForest package in R to predict the next event in a series of events (using ...
25 views

### Predictive model from ordinal panel data

Here's a hypothetical problem analogous to one that I am having trouble with: Prostate cancer biopsies are scored according to Gleason pattern (0-10). The scale is ordinal. Over 7 warrants surgery. ...
33 views

### rain cloud radar image prediction

I have a small pet project, which evolves around predicting a radar image of rain clouds given past radar images... My data comes from the radar images on following site: ...
80 views

### Why discriminative models are preferred to generative models for sequence labeling tasks?

I understand that discriminative models, such as CRF(Conditional Random Fields), model conditional probabilities $P(y|x)$, while generative models, such as HMM(Hidden Markov Model), model joint ...
228 views

### How to validate and compare models predicting a binary variable?

I have a question about determining which models are "better" and how to assess that info. Let's say I have three models, each which predicts our bid on won ping. Our bid is a continuous variable and ...
34 views

### A single model for multiple proportional response variables

I have a dataset that contains several morphological and biological characteristics of many bat species (90+). The dataset also has several variables that represent the diet. These dietary variables ...
30 views

### Need help finding a suitable online learning algorithm

I would like to build a system that attempts to predict which items a user would like, giving each item a "score". An item is really a collection of textual tags, and each item is presented to the ...
13 views

### Creating a subset of data to “normalize” the labels?

I have a set of data train that includes texts and associated labels: true or false. The label distribution is: 97% false, 3% true. I wish to detect the true labels, using Naïve Bayesian. Should I ...
30 views

### Should predictive buying models change when products/prices change?

My company creates logistic regression models that predict who will buy based on 1st & 3rd party online click data. We use this to target online visitors with interventions like retargeting ads. ...
47 views

### data mining/predictive modelling methods for small data sets

I have a small timeseries dataset that has 30 records with 6 predictor variable and 1 response variable. I would like to regress my time series response with 6 predictor variables. I have been using ...
253 views

### Finding the correct data mining approach

(I apologise for being a newb, but I'm a researcher introducing myself to data mining---any help or insight would be greatly appreciated. Also, this isn't technically a homework question, but I've ...
45 views

### Creating a high predictive value classifier

I have a two-class classification problem with n-dimensional data. I would like to train a classifier (preferably but not necessarily linear) with 100% positive predictive value. In other words, I ...
34 views

### Should CRT decision tree node be mutually exclusive?

I have been trying to understand the results of a CRT decision tree, my question is if the terminal nodes should be mutually exclusive? I am asking this because by reading the terminal nodes some ...
42 views

### Logistic regression - the model is significant in predicting the DV, yet the percent correct decreases [closed]

How can this be? My thoughts are that while the percent correct decreased from 80.8% to 80% with the model, perhaps the model is regarded to be a significant predictor due to the specificity having ...
46 views

### Caret package Varimp - feature selection question

I decided to use RFE using the caret package for feature selection for a logistic regression model. The documentation says the Varimp for linear model uses the absolute value of the t-statistic for ...
84 views

### Practically handling many non-stationary forecasting predictors

This question is about specific strategies to deal with non-stationary variables in forecasting. This problem usually rears its ugly head when you have a predictor whose levels are relevant to the ...
38 views

### Survival regression and prediction using median

I'm using artificially generated hazard curves (that is, I know the true hazard curve) and Aalen's additive model to fit the covariates. For example, below is an individual's hazard curve and my ...
109 views

### How to specify/restrict the sign of coefficients in a GLM or similar model in R

The situation: I'm struggling with a predictive analysis of food sales prices using a generalized linear model. My dataset contains different kinds of food (cheeses, vegetables, meats, spices etc.) ...
105 views

### What model should one use for this short time series?

Below I have quarterly total sales on the left (dependent variable), and a sample of the sales on the right. The two variables share a correlation of 98.7%. What model should I use to predict X? ...
23 views

### Building models with unequal intervals between time series observations

I'm trying to get into econometric/trading modeling and the universe of variables out there is immense. There are practically continuously updated variables (currency exchange rates, interest rates, ...