Questions tagged [predictive-modeling]
Statistical techniques used for predicting outcomes.
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Expecting your comments to structure my project?
I am developing an binary classification project. Initially I got a dataset including real data in 3290 rows and 15 columns. Then using CTGAN network I generated synthetic dataset with 100000 rows. ...
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Help with bsts model save
I am working on a projet where I need to make predictions using bsts package in r. I trained my bsts model and i want to save the model to use it instead of retraining every day, but when i saved the ...
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When can a low r-squared generate a good predictive models?
Most discussions on model prediction says that you should focus on error metrics, like RMSE, MSE, MAE or MAPE. Some even argue that r-squared can be low in a good model. However, I can't think of a ...
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Using a prediction from a First Principles Model in a second, statistical model to improve accuracy
I am trying to figure out what this is called, so I can do some reading on it and see which types of statistical models excel in this framework (and known pitfalls to avoid). I have been calling it a ...
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Live odds data set for horse racing [closed]
I am looking for a resource of live odds for horse racing to implement in my model. I know they exist, I just can't find anything that has worked, yet. Live, updated and accessible are what I'm ...
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Time series modeling tips
I'm currently building a pricing time series model for a category in produce and I have some questions. This is my first time building a forecasting model at my job and I've hit a few road bumps.
The ...
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How to model a marked temporal point process with unboundedly evolutionary integer event markers
I have a marked temporal point process (MTPP) where the number of discrete event types is unbounded. Each type of event occur several times and never happen again. For example, in a given time frame, ...
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python model to predict future performance
I would like to build a python model to predict how a student will perform on a given math test. I have data relating to each student and also their score on up to 100 previous tests that (each ...
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Impact of Adding Imbalanced Data on Model Performance for Different Groups
Suppose I initially have a dataset with 50 samples of type A and 50 samples of type B, each with several features. I built a neural network model using this data and recorded the prediction accuracy ...
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How to evaluate the performance of a prediction model across multiple predictions of the same event?
I was thinking of a hypothetical situation where you have a prediction model that can be used to predict the winner of an upcoming football match between Team A and Team B.
Say for the sake of the ...
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I need some advice about working as Mathematical Modeler/Data scientist [closed]
I have 10 years experience in studying mathematics in University, and I've just finished my Masters degree
I have some experience with LaTeX and Mathematica, what do I need to study to be able to ...
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How can I improve my predictive model?
Here is my interpretation of my model so far, I am investigating the relationship between ratings and followers on video games, but there is a problem. The more you get high ratings, the more you get ...
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Feature Engineering a Recency feature
I have a customer scoring problem I'm working on specifically on predicting conversion and coming up with a probability score on conversion (using xgboost classifier atm). There's a feature I want to ...
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Optimized input data structure for ML model training
I have a large dataset (20M+ rows) of user interactions which I want to use to predict the probability of a customer purchasing an item in one-, three- and six months time. However since the ...
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Random forest regression model for stock price prediction output has a flat line in the predicted values during the initial values
I have a random forest regression model for predicting the close price for stock data. I am getting model accuracy as like this:
/n Best Parameters: {'max_depth': 10, 'min_samples_leaf': 2, '...
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