Questions tagged [predictive-models]

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 more emphasis on performance.

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403 views

Figuring out probabilities with Hidden Markov Models

I'm really new to statistics so sorry in advance if this question does not make sense. Background: I'm trying to learn about hidden Markov models and they seem interesting but I was wondering about ...
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Can data processing time be estimated?

I'm curious if there are any analytical or empirical methods to estimate the time it would take to process a data set (grouping or various prediction algorithms). Known variables would obviously ...
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Log squared error accuracy justification: data mining competition

I was wondering what is the justification/rational for using the following error measure for judging accuracy instead of simply squared error? Link to competition: Heritage Health
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Difference between confidence intervals and prediction intervals

For a prediction interval in linear regression you still use $\hat{E}[Y|x] = \hat{\beta_0}+\hat{\beta}_{1}x$ to generate the interval. You also use this to generate a confidence interval of $E[Y|x_0]$....
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How can I apply models to predict the output of a test dataset using SAS?

I'm trying to use SAS from more of a machine learning perspective than a pure stats perspective. I want to perform resampling on a dataset to measure the predictive accuracy of a LDA and Logistic ...
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How to predict when the next event occurs, based on times of previous events?

I'm a high school student and I'm working on a computer programming project, but I don't have a lot of experience in statistics and modeling data beyond a high school statistics course so I'm kinda ...
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Difference between Step validation and Cross validation

I'm trying to model some chemical data from a series of spectra. I've gone through the preprocessing step and selected "autoscale" (I'm using Pirouette). And when it comes to validation I'm a little ...
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Interpretation of coefficients in polynomial regression for predictive modeling

I am building a predictive model (binary target variable) in the financial services industry. One of the (many) potential predictors I am adding to the model is related to the customers checking ...
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Predictive model for network data

Assume a network as a set of data, which are defined by their coordination $(x,y,z)$ and a weight on its edge. Now this data can be used as an input data to predict a single value. In my case, ...
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Canonical correlation and prediction

Is it possible to predict values of variables in a matrix Y from values of variables in a matrix X, ie. using canonical correlations since some variables are correlated among these two matrix? X and ...
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Bagging with oversampling for rare event predictive models

Does anyone know if the following has been described and (either way) if it sounds like a plausible method for learning a predictive model with a very unbalanced target variable? Often in CRM ...
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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 ...
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How to draw a random sample from distribution of prediction?

For my microsimulation, I want to use R to predict values and draw a random sample based on this prediction. To clarify my point: I want to simulate the number of chronic conditions people suffer ...
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What methods to use for statistical prediction/forecast of trading data?

I’m working on a trading system and need to apply some statistics on the results. Unfortunately I forgot all about statistics after I left university over a decade ago and now I really have no clue ...
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Is there a generic term for measures of correctness like “precision” and “recall”?

Suppose I am building some predictive models and then creating a report detailing how "good" those models were in various ways. Is there a generic (maybe even non-technical) term for the various ...
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How to predict shares?

Lets say I know what is the overall budget for some units and I want to predict share of budget each unit will get. I have historical data and could do regression analysis. Is it better to predict ...
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Machine learning techniques for time series estimation - forecasting price

Can anyone recommend any machine learning techniques for time series estimation? I have a series of times $t_{1}...t_{n}$, each having a set of associated features $f_{1}...f_{m}$, and a value $x$. ...
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How to test the predictive power of a model?

I want to build a model to predict the outcomes of experiments. My predictive model gives out scores with an range 1 to 100 values. I want to test if my predictive scores can be used to classify ...
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Least square estimation error, calculus question

I want to estimate $n+m$ parameters with the equation: $$\hat\theta=\left[\frac{1}{N}\sum_{t=1}^N \varphi(t)\varphi^T(t)\right]^{-1}\left[\frac{1}{N}\sum_{t=1}^N\varphi(t)y(t)\right]$$ where $\varphi$ ...
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Optimising control routines after creating a predictive model

I have a dataset with 1500 patients with data on recurrence of a disease. Follow-up time varies between 1 and 15 years. Approx 10% have recurrence. What I´d like to do is create a predictive model for ...
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How do you apply a linear regression built in SPSS to new data and generate prediction intervals

I am trying to use SPSS to build a linear regression on historical data (dependent and independent variables) and then apply this to new data (independent variables only) to generate predicted values ...
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Weight variables for predictive model

I received a question today that I wasn't exactly sure how to answer. I have built a predictive model using a fairly basic logistic regression that works pretty well and fits our business needs. ...
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Sites for predictive modeling competitions

I participate in predictive modeling competitions on Kaggle, TunedIt, and CrowdAnalytix. I find that these sites are a good way to "work-out" for statistics/machine learning. Are there any other ...
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How can you predict the likelihood of someone doing something given previous data?

I'm having a hard time explaining this (hence the weird and long title), also I'm not a mathematician, I have this data lying around in a database and was wondering how I could visualise it (and ...
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“Interestingness” function for StackExchange questions

I am trying to put together a data-mining package for StackExchange sites and in particular, I am stuck in trying to determine the "most interesting" questions. I would like to use the question score, ...
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Maximum of two (or more) gaussian distributions with known and possibly different means/variances

I am a software engineer by trade doing stats in my free time. I am playing around with an implementation of Microsoft's TrueSkill rating system for ranking players and openings in from a data set of ...
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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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Model performance metrics for ordinal response

I'm interested in assessing model performance on data with an ordinal categorical dependent variable. For my use case, the ideal metric would: Not assume equal intervals between classes or that ...
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Estimating event probability from historical time series with clear seasonality

I would like to predict the average number of days in a year for which two conditions are true: daily average temperature is below zero celsius the day was preceded by at least four days with daily ...
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Determining best fitting curve fitting function out of linear, exponential, and logarithmic functions

Context: From a question on Mathematics Stack Exchange (Can I build a program), someone has a set of $x-y$ points, and wants to fit a curve to it, linear, exponential or logarithmic. The usual ...
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Obtaining a formula for prediction limits in a linear model (i.e.: prediction intervals)

Let's take the following example: set.seed(342) x1 <- runif(100) x2 <- runif(100) y <- x1+x2 + 2*x1*x2 + rnorm(100) fit <- lm(y~x1*x2) This creates a ...
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Data preparation for regression

I am trying to predict real estate sales prices. In my dataset there are independent variables that are both nominal and numeric (square meters, prices etc.) Before feeding the data to any ...
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Looking for ideas to build a predictive model

I'm new to predictive models and I have a problem at hand that I need some advice with. Basically for a clinical application we want to predict the outcome of a rating scale with a model built on top ...
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Weighted discrete measurements of a value changing over time

The best way I can think to describe this question is by example: Imagine there is a ship sailing around the pacific ocean on an unknown path (possibly random.) Other ships passing by sometimes see ...
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Combining 2 sets of coefficients, weighting one of the sets

I have two sets of coefficients from similar data taken at different times. What I want to do is combine the two sets of coefficients giving greater weight to the more most recent set. The goal is ...
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How to produce a CI for a value predicted in CART?

My goal is to create CI for the CART prediction of new_x Consider the following code: ...
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390 views

Building linear model from exact variable measurements for use with noisy variable measurements

I want to build a linear model to predict a scalar output from a vector of noisy scalar variable measurements. I have two separate training data sets. One has output data and corresponding exact ...
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Survival Model for Predicting Churn - Time-varying predictors?

I am looking to build a predictive model for predicting churn and looking to use a discrete time survival model fitted to a person-period training dataset (one row for each customer and discrete ...
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Understanding the Pareto distribution as applied to wealth

The Pareto distribution can be used to give a pdf for the wealth of a person chosen randomly from a population. (In fact, this was its origin. See, for instance, http://en.wikipedia.org/wiki/...
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Manually calculated $R^2$ doesn't match up with randomForest() $R^2$ for testing new data

I know this is a fairly specific R question, but I may be thinking about proportion variance explained, $R^2$, incorrectly. Here goes. I'm trying to use the ...
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General approaches to model car traffic in a parking garage

a friend of mine has asked me to help him with predictive modelling of car traffic in a medium sized parking garage. The garage has its busy and easy days, its peak hours, dead hours opening hours (it ...
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When and how to use standardized explanatory variables in linear regression

I have 2 simple questions about linear regression: When is it advised to standardize the explanatory variables? Once estimation is carried out with standardized values, how can one predict with new ...
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Predicting long-memory processes

I'm working with a two-state process with $x_t$ in $\{1, -1\}$ for $t = 1, 2, \ldots$ The autocorrelation function is indicative of a process with long-memory, i.e. it displays a power law decay with ...
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Predicting from a simple linear model with lags in R

I have a dataset that I want to fit a simple linear model to, but I want to include the lag of the dependent variable as one of the regressors. Then I want to predict future values of this time series ...
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Predicting daily electricity load - fitting time series

I want to predict inter-day electricity load. My data are electricity loads for 11 months, sampled in 30 minute intervals. I also got the weather-specific data from a meteorological station (...
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ROC plot for continuous data in R

I am currently estimating a bunch of ARMA models, and using them to predict subsets of my data. In order to evaluate their predictive accuracy I would like to make some ROC plots, however since all of ...
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Predicting a semi-deterministic process

Say I have a process that gives me 3 outputs: $O^1$, $O^2$ and $O^3$. The outputs are generated from a semi-deterministic process, i.e. there is a deterministic component in the outputs, along with a ...
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Kappa for Predictive Model

The "standard" way to compute Kappa for a predictive classification model (Witten and Frank page 163) is to construct the random confusion matrix in such a way that the number of predictions for each ...
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How to predict Ozone concentration in few years time?

my friend is a chemist and his problem is to predict the level of ozone concentration in a single site. We have the data for the last 12 years. We want to predict the concentration for the coming ...
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Generative vs discriminative models (in Bayesian context)

What are the differences between generative and discriminative (discriminant) models (in the context of Bayesian learning and inference)? and what it is concerned with prediction, decision theory or ...