Questions tagged [predictive-modeling]

Statistical techniques used for predicting outcomes.

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6 views

Precision score (classification_report) 1/0 not predicting for 0 in logistic modeling using Sklearn

I have a binary outcome for an imported CSV file I am working with. I used the sklearn library to use the logistic model to gather predictions for my target value and also generate probabilities. ...
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21 views

How to restructure my dataset for interpretability without losing performance?

What I am doing: I am predicting product ratings using boosted trees (XGBoost) with a dataset in this format: What I want to do: I want to use SHAP TreeExplainer to interpret each prediction my ...
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31 views

Dealing with NaN for predictive models

I have data set that has data for patients: Arrival_Date : is when the patient has arrived Seen_By_Nurse : is number of minutes patient take to be seen by nurse since arrival when value is NaN it ...
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Beating Roulette with Neural Networks, YoloV3, and PyTorch

Background: I am in my last semester of electrical engineering, and I am working on my senior design project. The senior design project is a two-semester design project in which students outline, or ...
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12 views

Will the performance of my NER model improve?

I am training a spacy model from scratch by creating a dataset of my own with format spacy needs it to be in, the model is an NER model and the entity i am trying to recognize is Food items. I have ...
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23 views

SRGAN: Adapt the model to the input image?

I wrote and trained my own SRGAN: so I obtained a model that takes 32x32 images as input and gives their improved 128x128 version as output... I sent this template to Google Firebase Machine Learning ...
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20 views

Java or Python for training and implementing Predictive ANN models in production? [on hold]

What are your opinions? Should I use python since I'm comfortable with it and it is the superior language for machine learning, or should I use Java since it's what my company uses for all our ...
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18 views

How to handle a data set with large number (about 75%) of binary variables?

I am doing a research right now and want to classify (predict) churns of costumers using machine learning. My data set consists of about 500,000 observations with 20 variables: 15 are binary, 2 ...
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28 views

How to improve accuracy beyond optimal level? [on hold]

This may sound like an impossible task, but I believe it's possible in many cases. I have a tabular data set, with 341 columns representing independent predictor variables, and one column with the ...
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2answers
28 views

Time series modelling

I have daily data for 2.5 years , but with more data points as 0, so when i excluded them in the cases which seems to be invalid. Can i use any other model than models used in time series or should i ...
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1answer
19 views

Traditional Predictive Analytics vs Machine Learning Methods

What is the difference between traditional predictive analytics done using statistics and its tools and, one using machine learning and deep learning? How are we leveraging machine learning and deep ...
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36 views

Model should predict the same value every time for the same input

I have used a random forest model for prediction of prices. Should the model be predictable in its behavior? By this, I mean that I'm not changing the model and the input, Will the predicted value ...
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1answer
14 views

LightGBM choice of evaluation metric

I have past data of a large number of people who applied for a loan and their movement through 8 different stages, from start of application to loan being paid out. I am trying to build a model that ...
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32 views

Precision Vs Recall Curve analysis

I have the following averaged 𝑝𝑟𝑒𝑐𝑖𝑠𝑖𝑜𝑛−𝑟𝑒𝑐𝑎𝑙𝑙 curves with 4 models. Which one is the best?
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14 views

Hierarchical prediction

Suppose the problem is the following: there is, say, binary target variable $x$, and real-valued target variable $y$, which is only relevant if $x = 1$. What is the best way to train a model to ...
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1answer
20 views

How to predict consumer purchase in next 6 months?

I'm working on a model to predict a customer as being 'in-market' for a product in the next 6 months. The dataset has a wealth of information like lifestyle and demographic variables and previous ...
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33 views

Dealing with informative missingness

How can I deal with a time series that contains missing data which means something? So the value that is missing is not wrong. It's missing on purpose and imputing those missing values would mean a ...
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1answer
16 views

Time required to train a model based on features shape and CPU capacity?

How to estimate the time required time to train a model, given feature shape, CPU/GPU sepcs and type of model
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1answer
29 views

Difference between sklearn make_pipeline and imblearn make_pipeline

Can anybody please explain the difference between sklearn.pipeline.make_pipline and imblearn.pipeline.make_pipline.
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1answer
12 views

Deploy pretrained model to simple web app

As a small personal project, I wanted to try and deploy this image classification model with a simple web app (input image, output classification and heatmap). There are a couple pretrained models on ...
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3answers
55 views

Dealing with no data

I am working on predictive maintenance and get temperature data from assets. In few months or few days asset remains down and we do not get temperature value. In this scenario i cannot fill data with ...
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1answer
44 views

How to convert trained data (feature extracted) into a prediction model? [closed]

Background: I am analyzing and labeling some log data. (parsed already, sample data below) I have extracted the major features of data. For examples, the classification results ("1 - normal" or "0 - ...
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10 views

whether the LSTM network can be used to predict a binary outcome?

I have 6 set of time series labeled data which I want to use it to predict certain binary outcome. Is it allowed in the framework of LSTM model ?
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1answer
23 views

Modeling strategy for predicting a day/hour based on my dataset

This is my first time posting here. I'm usually on SO. So I'm not sure if these kind of questions fit into DS stackexchange. I genuinely need opinions on this. What data do I have - ...
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1answer
12 views

Appropriate model metric for a truncated response variable?

Here's a straightforward question I can't seem to find a good answer to. Let's say you're using some variables to predict age. I'm assuming a regression model is the right approach. In this case, what ...
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9 views

what are possible error analysis approach in tabular data?

I am working on binary classification on tabular data. The dataset is mostly made of categorical data and after fitting the data to a model I found test accuracy to be low. I want to do error analysis ...
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5 views

How is possible the result of GRU would other way around compared to LSTM while they were implemented samely?

Recently I crossed to a situation I can't figure it out why it happened. I applied six predictive models on a specific dataset as training-set and tried to predict the other similar dataset as an ...
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19 views

Getting Different Class output and Probability when predicting from model.predict and after deploying model with flask

For Binary classification problem,I am getting Different Class output and Probability for test data when predicting from model.predict and with deployed model with flask. In model.predict I am getting ...
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1answer
71 views

How to predict whether the client will renew the subscription or not based on given data structure

I have a requirement where I want to predict whether the client will renew the subscription or not. And the data is something like below. Basically client's subscription end date can be anything. ...
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2answers
27 views

ensuring that dependent variable decreases monotonically with independent variable

I have one key relationship between a numeric independent variable X and a numeric dependent variable Y, which is like a negative exponential function determined by 2 parameters. There are other ...
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12 views

Align data of different frequencies

My project's goals is modeling a physical system. Where I measure physical entities using sensors and try predicting future values. A problem I am facing, is how to align different sensors data in one ...
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3answers
30 views

How do ML model retain/store the learning(s)?

In other words, if the model after training and testing is ready for making future predictions, it must be storing the learning(s) somewhere in memory or disk or cache (or I really don't know). So, ...
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1answer
29 views

Can a Logsitic Regression model continue making predictions after removing predictions from the data set?

I have a logistic regression model that predicts churn (0 vs. 1). I was asked to use the model to predict on a historical group of non-churners, remove anyone who was marked as a churner, and then ...
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25 views

Can i use survival analysis to predict if a person will “die” or not, and then get the survival time if the person does?

I want to determine, given a project, "How long will it take for this project to be successful ?" Therefore, survival analysis seems like a perfect fit in this case (as I do have some projects that ...
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Poisson Model (w/ multiple levels X)

Question Is Poisson model the best method for predicting counts among multiple levels within nominal variable? Details Imagine data of 7000 observations, where output= Obs.Count {numeric,0,1,2..8} ...
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8 views

prediction with un-obligatory features

I am pre-processing a real-world dataset with some features with missing values. these features are not mandatory - the user doesn't have to provide them. This means the values are not missing at ...
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20 views

Predicting house pricing given a dataset consisting of [ location: date of transaction: price ]

What would be the right way to tackle the problem of predicting median house pricing, given that the data I have for training consists in a big list of entries that have the following values: ...
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31 views

LSTM model for many time series

Let's say one has many time series for which one wants to build a predictive model (based on LSTM). Which of the following cases would be more optimal and why? 1) building one model for all the time ...
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37 views

Combining the output of two models

I have two models that predict a person's activity (seating, walking, taking stairs, and sleeping) based on a person's motion and the video. Model 1 is trained on a ...
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12 views

Modify image with machine learning

Here's my problem: I already have a little neural network that generate images using DCGAN, that was very entertaining to do but now I'd like to modify images using ML methods. Let me explain myself: ...
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22 views

Significance of AUC score

My model (Logistic Regression) has AUC score of 0.8 Am I right in stating that the probability of the model ranking a random positive sample higher than a random negative sample is 0.8? Also, how ...
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1answer
18 views

Identifying importance of each feature in deep model

I have a deep model and I want to figure out which feature has the maximum influence on predicted result. For this I train the model with all the features I think are important, during prediction I ...
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25 views

Alternatives for categorical prediction

Upfront question: What are some alternative methods for predicting categorical data? Details: I routinely process data that is 100% categorical. Almost always, this data is nominal (while, ...
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14 views

Getting Error while predicting during deploying simple ML model with Flask

I have deployed a simple titanic (doing for testing purpose) model with Python Flask. I am using below server.py (Flask app start and predict API code) and request.py (JSON request) code. Getting ...
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2answers
51 views

Which predictive model is appropriate?

I'm completely lost when trying to choose the type of predictive model for my problem. Is it autoregressive model, nonlinear time series, Markov Chain or other? Can someone please give me some advise? ...
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Checking if a LSTM model is running in the back

I am trying to reproduce the following tutorial, using my own data. The aim is to build a RNN model, which has three LSTM cells. I've run my script and I had some results. When I rerun it to plot my ...
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8 views

What is the best activation functions to use to solve my problem?

I am using python with TensorFlow backend. My data is sets of 100 numbers between 0 and 100, and I need to predict whether the next number after this series is higher or lower than 50. What I have so ...
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24 views

Any idea on how to model this specific data distribution. See attachment

I am trying to fit a curve on the data( in the attached image). I see that there is a lot of variance in the response variable for each explanatory variable value. I am not sure how to model this. I ...
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Why do you need to use group lasso with categorical variables?

From what I've read you should you use group lasso to either discard the dummy encoded variables (of the category) or use all of them. If you use normal lasso then some of the variables in the group ...
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31 views

How to test model accuracy on new vs. historical data?

I created an XG Boost model to predict churn using a dataset of customers who were sold during 2018. The accuracy of the model is 89%. Does it make more sense to re-pull the 2018 dataset, where more ...