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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Quantifying applicability domain for predictive models?

I have a big dataset and I want to build a classification model (svm, rf, ann etc.). Then I split the original dataset into training set and test set. I build the model using training set. After it ...
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29 views

Computational Complexity of Prediction using SVM and NN?

I've seen answers discussing the complexity of training SVMs and neural nets, but how about for predicting new responses once a model has been trained? For context, I'm working on an app that should ...
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21 views

How do we use logistic regression (scikit-learn) to predict values

Logistic regression can help to predict a value whether it would happen or no. I'd like to know how can I do that using sklearn. I'd like to know the probability if this event would happen or no. I ...
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25 views

Hidden Markov Model: Predict observation sequence from state sequence

Given a transition matrix, starting probability, means and covariances Is it possible to predict the most likely observed sequence for a given state sequence using the above details? If yes, how? ...
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14 views

How can we predict random non-balanced events?

Prediction is the ability to statistically foretell the occurrence of future events by learning from historical data. In all the cases, if we have a large enough sample of data on how people behaved ...
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28 views

Which machine learning method to use for geographic systems prediction?

I am trying to do experiments on geographic systems prediction. We're working on classifying the location where we sell product most. So, we need to analyze the hestorical data and predict the success ...
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15 views

How do interpret statistically NULL SVM Output

I am using LibSVM (3.18) as an implementation of SVM. But every time when I'm predicting the result, it's giving zero. I am following these instructions: I have CSV file (+50K lines), Most of data ...
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64 views

Finding an equation with many variables to fit a set of data

I am writing a program which takes notes from a keyboard as the input, (just numbers, 1 to 88) and decides which notes are played by which hand. There are a lot of variables, for example, the position ...
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21 views

Comparing nested, non-linear models

I would like to compare the fit of two non-linear regression models: 1) $$ Y = (\Pi^{10}_{i=1}\beta_i^{x_i})^{1/\Sigma \beta} $$ 2) $$ Y = \begin{cases} (\Pi^{10}_{i=1}\alpha_i ...
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44 views

Regresssion of Accurate Data

I'm collecting calibration data for a device which involves three variables $S$, $L$, and $x$. For a given coordinate $(S, L)$, the device will provide me with the corresponding value of $x$ to a high ...
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2answers
27 views

Cox PH model selection and validation

I am trying to analyze my data using survival CoX PH in SPSS v.19 and also attempting to make different prediction models (without and with a biomarker of interest). I am a clinician (not a ...
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10 views

How To Fix a Non-Representative Sample Using Ordinal Logistic Regression and Predict Appropriately?

After searching for this question, I did find this -- but it didn't seem to be asking the same question and I'd like to extrapolate on it if possible to get more into fixing it generally and the ...
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29 views

How Can I Make Sure All My .CSV Data Gets Imported as NA instead of Blank in R? [migrated]

In my dataset, I'm using have four assessments I'm trying to predict: 1 [Good] to 4 [Bad]. My model seems to be working using the polr function to predict values ...
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7 views

Calculating variable importance at the individual prediction level

I'm trying to build a model which shows the significance of each feature in contributing to the score of each individual prediction. As a dirty hack, I'm running a logistic regression with ...
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1answer
11 views

Is it possible prediction of chemical activity with few data?

I have activity data (represented by a real number) for five chemical compounds (and for which I have a set of 600 descriptors) and would like to use neural networks or SVM or any other system that ...
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1answer
40 views

How do we predict rare events?

I am working on developing an insurance risk predictive model. These models are of "rare events" like airline no-show prediction, hardware fault detection, etc. As I prepared my data set, I tried to ...
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20 views

Are trend/cycle filters intended to be used in predictive models, or just analysis?

I am relatively new to time series modelling and for a task I have I've had good success (in terms of forecast error) by first splitting the data into a trend and cycle components using a ...
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30 views

Neural net model - error during training

I'm getting started with R, I really like it but recently I found myself in a corner. I'd like to build neural network model that predicts heat consumption. I have historical data that contains ...
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45 views

How to gently introduce epidemiologists/public health coworkers to advanced predictive modeling?

Coming from a social science and epidemiology background, my coworkers were trained on least squares regression, logistic regression, and survival analysis. They like to see 95% confidence intervals ...
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22 views

Finding what change in each variables equates to the same impact

I hope this is even possible. I'm doing some stats on a fantasy basketball league I am in. Let's assume I have the totaled stats for the week for each team in a pandas dataframe. It looks something ...
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23 views

Literature for prediction models where each training example has a different amount of data?

This could be a machine learning question as much as a statistics question, but I think this is the best place to put the question. Here are three different examples of problems where each ...
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27 views

How to model to improve the room usage efficiency based on motion sensor history

To reduce the confusion, I changed my application from traffic to meeting room, so this application is about modeling a meeting room efficiency , the data collection is built by placing a kind of ...
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12 views

Predictive Model with Underlying Environment Trending

I'm looking for some ideas / perspectives on what can be done when a predictive model is being trained on sample data that is taken over a period of time and the underlying environment is changing ...
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37 views

Cost Benefit Analysis of Pre-screening Widgets for Faults before they Fail

I want to build a model that determines whether to pre-screen my widgets for defects. If I do pre-screen, it costs a fixed amount per check and I resolve the problem 100% of the time. If I don't ...
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70 views

R: plotting a prediction model and understanding results

I am experimenting with developing a linear model lmodel1 which predicts a temp response variable, given three independent ...
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8 views

Predicting the growth of a social network

I am building a predictive model for the growth of the amount of users of a new p2p protocol inspired by bitcoin and I would like to use historical data collected from the growth of major social ...
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53 views

R: multiple linear regression model and prediction model

Starting from a linear model1 = lm(temp~alt+sdist) i need to develop a prediction model, where new data will come in hand and predictions about ...
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51 views

Suggest models for prediction based on small sample data

I am not a traditional statistics guy. I am from an electrical engineering background. So, spare me for lack of jargon. The model is to be used for predicting agricultural output based on previous ...
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24 views

How to determine the factors correlated with observed data?

I have box-office collection data on a number of movies. I also have the production budget, director name, lead actor, actress, language and other meta data related to the movie. I want to know which ...
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11 views

How to calculate performance statistics of continus learning model?

I have continuous weak stationary process that I need to map on logical result value (0,1). For example I want model that in 2 ways: logistic regression native Bayes classificator I want to know ...
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80 views

How many people bought wine?

Rephrased a problem trying to solve for work in terms of people buying wine, also included progress made so far. Set-up: Customers enter a winery with the option of buying bottles of wine. Those who ...
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15 views

Which method(s) for forecasting time series of event durations

I have the $N$ individuals each observed for $T$ days. For each individual I have some basic demographic data. Each $n$ individual, during the observed time $T_n$ may experience event $E$ which is ...
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89 views

How to do external validation of logistic regression models and perform model benchmarking

Quality assessment in trauma has for > 25 years been done with the US derived logistic regression model, the TRISS model. DV: survival/death and IVs: physiologic derangement (continuous), anatomic ...
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2answers
106 views

Are there any probabilistic models for graph-based recommender systems?

All I can find now is somehow based on random walks or graph kernels, which is nice, but I want to have a more or less solid probabilistic foundation for my recommender system for bounds and ...
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9 views

Feature importance and interpretation of alternating decision trees

Is there a way of calculating feature importance in alternating decision trees? What if I've already trained an alternating decision tree and want to calculate feature importance in terms of ...
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47 views

ARIMAX for modelling daily sales

I am trying to model daily sales for a take out restaurant. They are only open on business days - no holidays or weekends - as their primary clients are office workers on their lunch breaks. Below is ...
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21 views

building a feature set for scikit learn

Im using RandomForestClassifier for a probability prediction task. I have a featureset of around 50 features and two possible labels - ...
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10 views

Statistical analysis and prediction of variations in anatomical features

I am doing a statistical analysis of variations in anatomical features, for example the shape of a pelvis bone. I found out that morphometric method can be used to quantify differences in geometry ...
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20 views

Time Series Forecasting Method to use both Predicted and Predictor variables

I am learning Predictive modeling and building a Forecasting model to predict Insurance sales in US as a part of my academic project. I want to do Time Series forecasting. I have Y(t) as my response ...
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11 views

Bias in predicting survival with time varying covariates

I'm trying to predict survival probabilities with time-varying covariates. My dataset constitutes a variety of subjects who enter the study at different dates and receive multiple follow-ups. For each ...
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1answer
81 views

predict function and categorical variables in R

This is more of a general question about how the predict function treats categorical variables and how to interpret the output from predict. I have a zeroinfl model to predict the number of animals ...
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112 views

Time series prediction: visualising path uncertainty region

I am predicting a time series' future evolution and am evaluating the path uncertainty using bootstrapping. Is there a good way to visualise the uncertainty that goes beyond simply plotting a pair of ...
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85 views

Short term road traffic forecast modeling using neural networks toolbox in matlab

I have a hourly time series data of road traffic (i.e. count of the number of vehicles passing on a particular segment of road) collected over 7 days a week (Mon to Sun) for two weeks starting from 9 ...
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79 views

Discrepancy between log likelihood Harrell's C Index and brier score for the evaluation of a Cox regression

I am evaluating a dataset of ~400 subjects and 10 covariates trying to fit a Cox ph model for predicting survival in AML patients. To evaluate the models I am using a bootstrapping procedure of 50 ...
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27 views

Building prediction model with estimated predictor variables

I'm planning to use logistic regression with multiple (~5) predictor variables to predict whether something happens or not. I have two types of predictor variables: known (measurable) variables and ...
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38 views

Prediction with categorical and numeric variables

I used R to estimate a regression with both numeric and categorical variables, and obtained coefficient estimates. However, when I try to make predictions using new data, there appear to be some ...
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34 views

Data mining of time series

I have a dataset which consist of n time series variables $X_1$..$X_n$ , and a time serie output $Y$. I would like to mine the data to find if some functions (lagged or not) of the $X_i$ can predict ...
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32 views

Comparing 2D heat maps of observed data to 2D model predictions

From "How to ask a statistics question": PROBLEM you are trying to solve: Given two-dimensional heat maps of responses (DV), choose the 2D model (also a heat map, but can have different ranges of ...
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2answers
35 views

Selecting features and estimating their out-of-sample performance with cross-validation

I have only a small dataset. I want to 1. select the most predictive features out of a large candidate pool and 2. get an estimate of their expected predictive performance. In the elements of ...
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222 views

Cross-validation and feature selection of a multivariate regression

I've been trying to create a multivariate regression model to fit my training data into the prediction of a value. I've put my data into a matrix X with ...