Questions tagged [prediction]

Prediction of unknown random quantities, using a statistical model.

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17 views

How can I identify the appropriate variables for a prediction model using linear regression?

I need to create a predictive model for the pricing of Airbnb using a linear regression. The data set contains 34 variables and I do not know which of them are suitable. I have already divided the ...
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Bachelor Thesis: ML Soccer prediction - what model?

I am starting with ML and am kinda lost. My Bachelor Thesis revolves around the prediction of soccer games and my mentor thought it would be fun to do that with ML - interesting yes, fun not so much. ...
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Why is logisitic regression predicting TRUE values at a much higher rate than in the training data?

I am trying to use logistic regression to make predictions in R. I am confused as to why a model is predicting TRUE for 90% of predictions, when the training data ...
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1answer
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Definition of predictive hazard function?

In a Bayesian context, the posterior predictive probability density function is $$f_p(t) = \int f(t\mid \theta)\pi(\theta\mid \text{Data})d\theta,$$ where $\pi(\theta\mid \text{Data})$ is the ...
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time series prediction model with minute data

I m trying to apply prediction at my data that is taken from the sensor after 15 min ...
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15 views

Organizing Data for hourly and daily predictions

Let's suppose I'm using SVM (Regression) to predict variable y and I have multiple input variables (x_i) which are data from sensors at intervals of 10 minutes. From an operational point of view, I ...
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31 views

Predicting a Markov chain next state using previously predicted states

Suppose we have a Markov chain with two states A and B. This associated transition matrix is: \begin{equation} P_{mc}= \begin{...
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16 views

Predicting game outcomes with moving averages of goals scored

I decided to make a sports gambling script so I could quit my job and never work again. I just started and I read about Poisson distributions (which kind of approximate the chance of X goals getting ...
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20 views

Why does the RMSE value goes high? [duplicate]

I have been trying to predict the glucose values of patients by using regression algorithms. I used Support Vector Regression (RMSE: 65), Logistic Regression (RMSE: 86), Linear Regression(RMSE: 64) ...
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Is there a guide for when to implement time series techniques?

I am interested in getting a better sense as to when to use time series techniques. Let's say you have a data set with units sold as the response. Your goal is to predict units sold on any given ...
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Manually predict lognormal survreg model - R

I'm analyzing environmental data using the "NADA" R library, which relies heavily on the "survival" package. I am dealing with left-censored data, which are nonetheless strictly positive. To deal with ...
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Time series model for cryptoprice prediction

I am fairly new to the topic of statistics and data science. My first dataset consists out of the BTC prices since 2013 per minute. The second dataset consits out of posts from a social media platform ...
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Explanation(s) for unimodal distribution of prediction probability computed by Random Forest

I have a typical binary classification problem with a sample of ~700 instances where I fitted multiple classification models including logistic regression, SVM and Random Forest. The instances are ...
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Small size independent observations

I am looking at sports team level data (summarized by average in each season) over several seasons and would like to predict/classify the winner of the championship. In a single season, the data has ...
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15 views

Predicting in Cox’s time varying proportional hazard model (theoretically as well as using Python)

Are there any ideas on predicting the remaining lifetime (say at time $t_0$) in Cox’s time varying proportional hazard model? Im interested in theoretical ideas as well as practical ones for the ...
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1answer
43 views

Predicting probability of non-payment for vehicle loans up to 90 days in advance

So I have an interesting problem that I'm working on. I have a dataset of customers from a bank for car loans. For each customer, I also have their associated payment information including repayment ...
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32 views

Predicted probabilities very close to 0 and 1 in GLM model

I've added new attributes to the binary GLM model. AUC climbed to 98%, logistic loss decreased to 0.45. Training set has ~50 cases. I can see that predicted probabilities are extremely close to 0 and ...
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9 views

Performing classification when the potential options of classes are different for every data row/user

I have a problem that I am trying to solve using ML but am not able to determine techniques, hence asking for advice. Appreciate your urgent response! I have a dataset of several users. Each user has ...
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14 views

Deriving variance of prediction error for mean prediction

A regression model yi = a + bxi + ei is given. When a single value of xi0 is observed, the model is yi0 = a + bxi0 + ei0. The prediction variance for a single out of sample prediction is sigma^2* [ ...
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1answer
34 views

Out of sample prediction

I have a model in which I estimate the impact of price on acreage. My data is composed of 10 years. So I use these 10 years to estimate the model and get to coefficients. In next step, I want to use ...
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How do I set a benchmark for a laboratory measurement from known data?

A colleague is trying to gain formal control of a laboratory process and needs my help. The process involves transferring a liquid into an empty vial using a qualified liquid delivery device (e.g. ...
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23 views

Learning from “similar” data points

Suppose we have predictor variables $x_{i,1}, x_{i,2}, ..., x_{i,m}$ and a response $y_i$ for $i = 1, ..., 1000$. However, $y_i$ is inherently stochastic in nature, and needs to be represented by ...
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63 views

Expected prediction error pointwise minimization

I am reading "The elements of statistical learning" book by Hastie and have one question about the expected prediction error. He defines it as the following function (section 2.4): $$\mathrm{EPE}(f) = ...
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Validation accuracy jumps badly between 0 and 1

Issue: My validation accuracy jumps between 0% and 100%. This seems fairly implausible to me because the predictions are between two classes only and I am validating on full valSet (41802 records) ...
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33 views

Time Series Analysis for Coordinates using LSTM

I have a dataset in which ids of locations connected with corresponding latitudes and longtitudes. I want to predict next location of the activity after training my LSTM model. However, feeding the ...
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1answer
21 views

Which is the decision rule in a gda classifier?

On the text book there is the following formula for the prediction rule, but I don’t understand where it comes from: The textbooks says it had been derived from I suppose pi and theta are the ...
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How to perform a classification model on clusters derived from cluster analysis

I'd like to compare whether classification models using a clustering technique before classification gives better predictions than classification models without clustering. Quite similar (but more ...
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Interpretation of Adjusted Predictions Contrasts (Margins)

I would really appreciate some help with interpreting results for contrasts of adjusted predictions (I use Stata 15, margins command). I run an experiment and fitted a regression model comparing the ...
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1answer
26 views

Does it make sence to use an instance id as a feature to train a ML model?

I'm trying to predict a footbal outcome by training a ML model. My data have team IDs along other feature. The question is, will it make sencce to feed it (the model) the team IDs or will it treat it ...
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1answer
30 views

How to improve Recall and Precision?

I am working on a big data set which has 25 features with 237862 number of rows. I am trying to predict return . 1 is for return and 0 for no return. My data set has 12% of data which returned. So ...
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16 views

How can i define a range of correct answers for an neural network, that predicts a continous value?

Take for example a NN that predicts the height of an animal. If the NN predicts a height within +/- 1 cm of the actual height the answer would be correct. I can not find options for this in e.g. Keras....
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27 views

Predicting the variance of a future sample

Suppose that I have the dataset for wealth distribution for 50 different countries. Each country's data consists of the wealth figures for 100 random individuals in that country. Some countries have ...
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21 views

Can I use RMSE as a percentage of error

I'm hoping someone can verify my assumption. I am building a regression model against an outcome variable which is a percentage. After tuning, the model outputs an RMSE estimate which I've looked to ...
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1answer
37 views

Is the objective of Principle Component Analysis mainly for prediction rather than interpretation?

PCA assigns more weight to the variable with high variation. However, the factor's variation is not the same as its importance. For example, suppose the true model is y=3x1 + 100x2, which shows that ...
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Reviewing my method for making daily predictions based on past data

I'm trying to build a model for a personal project and would like to run my approach by you guys to check it's validity. I will be making a prediction at 0900 every day(t), and am trying to observe ...
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20 views

Is there any proof that clustering algorithm reduces forecasting error?

k-means clustering algorithm is very useful for forecasting a future value (in a sense of time-series) by allowing estimation only within a chosen cluster. I can intuitively admit that k-means ...
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… This is random, right? [closed]

The X and Y axis are predictor variables, and the response is 1 (the + sign) or 0 (the circles). I shouldn't explore this further, right? There's no way to predict for 1's?
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Weighted OLS predictions

I am experimenting with cross validation to determine a cap for weights in weighted OLS (because the weights become large). I first estimate $\hat{\beta}_{trn}$ using the training data. Do I (A) ...
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1answer
29 views

Employee churn as time-to-failure/survival analysis?

I have an employee churn problem where I have data for every three months of employees in a company ranging from 2015-2019. Does it make sense to model this problem as a time-to-failure/survival ...
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1answer
53 views

Predicting in Structural Equation Modelling

So I would like to do some basic predictions with the SEM model I have produced. So far I've come across 'lavPredict' but i'm struggling to work it. ...
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1answer
36 views

Best Linear Predictor Assumptions

Chapter 6 of Plane Answers to Complex Questions, 4th Edition motivates linear regression through the lens of best prediction. Unfortunately, I'm confused about some assumptions in deriving the best ...
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1answer
33 views

If the correlation of X and Y is high, the probability of correctly predicting Y from X is also higher?

We usually use the concept of "regression" to describe that variable Y can be predicted from variable X. But can I surmise "correlation" involves the same idea ?
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1answer
16 views

I need to predict the counts of ticket in coming years and the data I have are:

I need to predict the counts of ticket in coming years and the data I have are: 1.Month 2.Counts for previous years 3.Domains on which the tickets were raised. I used input features as Month and ...
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2answers
45 views

Best model for data-based predictor selection (Regression, R)

I would like to figure out which of 24 predictors serve best for predicting a continous outcome. I have a data set of 252 people, but only 150 people with full observations (without missings). I've ...
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1answer
32 views

Correlation between features in time-series

This is a technical/conceptual question. I am not sure if this is the right place to ask. If not, please let me know, I will change it. Question: I have some time series data with 12 room ...
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Poisson Binomial Distribution - confidence intervals for sum of unequal probabilities estimated with uncertainty

I believe my question is related to, but distinct from this one: Poisson Binomial Distribution - confidence intervals I am working to estimate species richness by summing the results of 12 individual ...
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1answer
33 views

Time series when seasonality appear due to both solar and the lunar calendars

I have a time series data as shown in the figure below where the X axis is the serial number of the day of the year form 1 to 365 where 1 is 1-Jan and 365 or 366 is 31-Dec. The Y axis represents the ...
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2answers
46 views

Any suggestions for a small complex dataset with a binary outcome

and thanks in advance to anyone who helps me out here! I am working with a small and complex dataset: Approximately 14 patients who underwent surgery for a mental health condition. I have very complex ...
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1answer
22 views

Forecasting a not-seasonal time series in R

I would to forecast a not-seasonal time serie in R. This is my serie and the model built with HoltWinters: ...

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