Questions tagged [predictive-modeling]
Statistical techniques used for predicting outcomes.
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Weighting in an attrition model
I am building a test model that predicted likelihood of leaving a company. The data I have is very recent, how would you weight a model to account for how long they are at the company. I wouldn't want ...
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How to Predict Probabilty that the Customer will buy specific Product?
We have data consist of previous transaction history consisting of Date,Order-id, Product-id, Product name, ordered or not. We need to predict a specific product probability for all the customers that ...
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Newbie in ML - Using error traces to predict issues
We have trace data from Jaeger which shows end-to-end information about requests/transactions/error codes. Jaeger UI/APIs are useful in debugging issues after they have happened. The requirement is to ...
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MLOps for beginner
I am 1 year old in ML and have been using jupyter notebook to build static models all these days, do some analysis and present my results to the bosses as it was all POC.
Now, we would like to scale ...
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Regression with angles as response variable
What are some general approaches to regression/prediction problems where the outcome variable is a vector of angles?
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On-Device Football Detection Model not performing up to the par ; misdetections
I have trained a football detection model. I have so far trained the models using RCNN, SSD (backbone MobileNet), CenterNet and others. SSD and Centernet, so far have been the best in terms of speed ...
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Why does model with hyperparameter tuning underperform?
I have a dataset where I applied xgb model with grid search to tune the hyperparameters and class balancing. I compared the model without any hyperparameter tuning with a model that has been applied ...
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Why can Random Forest "handle missing values and cardinality well compared to linear regression"?
I've read a question comparing Linear Regression and Random Forest Regression. I was supposed to choose between then and solve a problem (=predict prices). The question mentioned that "Random ...
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Capacity planning and modelling
I have a business case in which I am going to model how many devices are required given the predicted workload in a series of monthly cohorts in the next ten years.
The work could come from multiple ...
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How can I combine (or not) multiple datasets for training a model
I am trying trying to predict if a customer is likely to churn or not.
I have multiple datasets, from multiple different customers, of which some have churned and some that have not.
I am trying to ...
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Using Latitude/Longitude and site ID in classification of daily air pollution levels
Assume that there is a very large dataset of hundreds of sites which contains only the PM2.5 level, the site ID, and the Latitude and Longitude as features. The independent feature to be predicted is ...
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Which Model for predicting flight delays is appropriate except Random Forest and Decision Tree? (Monte Carlo?)
Im studying M.Sc Data Science and in the module "Decision Support Systems" me and my group have to make a presentation. Our Proposal is the following:
Background
With generally high demand ...
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How to use LAT/LNG as predictor variables
I'm working on geographic data where I need to predict the average income per geo key/zip code. The data I have consisted of more than 30 million unique geo keys in Zip+4 format. As per my ...
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Marketing Spend Optimization Techniques
I need some help with market spend optimization. I’m working with a client who’s running an offline operation that’s primarily driven by online marketing (fb, google, twitter etc). They had asked me ...
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What should be the target vairable in CTR maximization problem?
I have a dataset that contains some user-specific detials like gender, age-range, region etc. and also the behavioural data which contains the historical click-through-rate (last 3 months) for ...
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Random Forest Classifier Output [closed]
Used a RandomForestClassifier for my prediciton model. But the output printed is either 0 or in decimals. What do I need to do for my model to show me 0 and 1's instead of decimals?
Note: used feature ...
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Interpreting cluster variables - raw vs scaled
I already referred these posts here and here. I also posted here but since there is no response, am posting here.
Currently, I am working on customer segmentation using their purchase data.
So, my ...
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Plotting decision boundary from Random Forest model for multiclass MNIST dataset
I am using the MNIST dataset with 10 classes (the digits 0 to 9). I am using a compressed version with 49 predictor variables(x1,x2,...,x49). I have trained a Random Forest model and have created a ...
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How to compute threshold?
I would like to detect anomalies for univariate time series data. Most examples on internet show that, after you predict the model, you calculate a threshold for the training data and a MAE test loss ...
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Dealing with little available data: transfer learning
Suppose I seek to predict a certain numerical value, whereby the data set which contains the predetermined correct labels is only very small. However, I'm also provided a large data set with a label ...
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Can classification model B trained on data labeled by classification model A exceed the performance of model A?
Let's say that I have a small or medium sized dataset of images, say 50,000. I use transfer learning to train a deep learning classification model. Call this model A. Model A is deemed to have good ...
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What model and attributes would be good for this data?
I have the following set of data like in the picture, with 366 Temperature values for one year. The first set of data would be for training and the second one for test. I would like to detect the ...
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Which machine learning technique can be used for predictive log analysis
I have log data with 100k records. And
These parameters.
It looks like this. message types can be helpful for anomaly type detection. Out of total 15 message 5 ...
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Where should I find electrolytic capacitor ageing data
I am trying to get a dataset of Electrolytic capacitors ageing and I am not being able to find one that shows the ripple current and the voltage in order to calculate its Equivalent Series Resistance (...
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LGBM model predicting only single class on unseen data!
I have built a LightGBM based machine learning model on data of molecules of two classes. The distribution is as follows. Class 0 has 5933 data points and class 1 has 4696. The train test accuracy I ...
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Explanable AI ! Is someone facing this issue? What are you doing to solve this problem
Is anyone here dealing with the problem of explanable AI? i.e. how are you able to understand and interpret predictions made by your machine learning models. Anyone here facing this problem or already ...
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how to deal with features in pairwaise comparison models?
I am working on a dataset of ATP (Association of Tennis Professionals - men only) tennis games
over several years. I want to predict the outcome of tennis so one way to do that is using a Bradley-...
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Analyzing series of events
noob in data science here.
I would like some advice on the following: I have a series of events that can happen at random times of a day, there is the event start/end time. If an event started already ...
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Labelling for churn measurement
I have 3 domains of supplier data (Jan 2017 to Jan 2022) and they are as follows
a) Purchase data - Contains all the purchase (of product) data made by the suppliers with us. It contains columns such ...
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Multivariate multiple input batch data regression
So, in general, my question is how to approach modeling with this kind of data.
I'll try to explain the challenge and some of my thought process.
Challenge
I have batches of cars sold. One batch may ...
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What kind of ML technique/models is suitable for finding relationship between sets?
Suppose of list of two entity sets:
...
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Model transfer with limit to none label information
I have this problem I hope to get some help here.
Say I have a type of product A whose measurements are X_A and an outcome property is ...
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What is the correct way to sample from a large dataset with several years of data?
I'm a student doing a machine learning project. I'm using the Lending Club Dataset 2007-2018 to predict loan default. The original dataset contains over 2 million rows. I want use a sample from it to ...
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What Model would best be suitable for my dataset?
I am kind of overwhelmed with the amount of models there are so finding the one that best suits my dataset is proving kind of difficult. The Dataset I have is as follows
, its produced by a Radar, ...
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keras binary classifier is predicting same outcome and has very poor AUC
I tried to build a binary classifier for a dataset with 298 binary factors and 1 predictive binary outcome, but the predicted values for the test data are all the same. My code is:
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Models: during training and during deployment
It's known that during the model training, we hold out the test-set. However, I actually find during deployment, that if to use a new model train on the entire dataset (train+test), actually yield ...
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Clustering - Auto ML Solutions
I intend to use clustering for my problem grouping customers together. However, instead of me manually tuning hyperparameters and CV, I would like to know is there anyway to do the clustering using ...
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How do I decide the frequency of data capture for modeling? How does it affect my final model?
I plan to capture data to predict energy consumption in a food processing plant. I want to capture production details such as how much each category of food is produced, what is the machine's output, ...
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How to export shap waterfall values to dataframe?
I am working on a binary classification using random forest model, neural networks in which am using SHAP to explain the model predictions. I followed the tutorial and wrote the below code to get the ...
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step-by-step creation of models with accumulation of predictors vs GridSearch
Can you please tell me if step linear models of the independent variable "ols_step_both_p()" (R) are possible with the accumulation of predictors in the amount of 58, 220 and 299, naturally ...
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Assess overfitting - All model metrics or only specific metric?
I am working on a binary classification using random forest with 977 records with 77:23 class proportion
I got the below performance in train and test data (AUC = 81)
Train data
Test data
My metric ...
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Sample size for SHAP explainer and range of a SHAP value
I am working on a binary classification with 977 records with 77:23 class proportion. I used random forest model.
Based on my attempt to run SHAP package, I got the below plots
And I also see that ...
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Can I use Variational Autoencoder/GAN for image manipulation?
I have a CT image with the tumor and the corresponding Radiotherapy image. I want to predict the CT-Image with the corresponding change. For my training, I do have input CT image, Radiation therapy ...
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Dummy Predictors / Continuous Dependent Variable
I have a dataset with 50+ dummy coded variables that represent the purchases of an individual customer. Columns represent the products and the cell values 0 or 1, whether the product has been ...
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Why does gridsearchCV fit fail?
I already referred this post here but there is no answer.
I am working on a binary classification using a random forest classifier. My dataset shape is (977,8) with 77:23 class proportion. My system ...
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Measuring performance of customer purchase predictions
My goal is to develop a model that predicts next customer purchases in USD (Update: During the time period of the dataset, if no purchase was made by the customer, the next purchase label is set to ...
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Lagged Features
Lets look for example, at the forecast the sales of a retail outlet.
If I understood the concept correctly, than a lagged feature would be the sales of a previous month t−1.
Would it make sense/is it ...
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How to interpret SHAP summary plot?
I already referred these posts here and here. So, please don't mark it as duplicate
I am doing a binary classification using random forest and class labels are 1 and 0. What is the likelihood that ...
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Fashion Compatibility Performance Evaluation: High in AUC but Low in FITB
I am a newbie in deep learning field. Still trying to understand how this works.
But now I am working on fashion compatibility prediction.
The most well-known performance evaluation in this task is ...
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