Questions tagged [feature-engineering]

Question 1

I am working on some natural language stuff for fun, basically a rhyming dictionary, trying to figure it out. Trying next to figure out how to properly/decently capture the basic consonants + vowels ...

Question 2

What I’m trying to figure out I'm working on a machine learning project and would love to hear your thoughts on two things: A. How to prioritize feature exploration B. Whether to fix hyperparameters (...

Question 3

Beginner ML practitioner here. I'm trying to do some time series forecasting on a fairly high resolution dataset that stretches over a long period of time. The values vary pretty widely over time: to ...

Question 4

Question: Are there better approaches than regex for extracting event dates (including relative) from noisy text? Are there NLP tools that can help disambiguate multiple date mentions in various ...

Question 5

I am building a random forest regression model. The goal is to predict the maximum each customer will spend in a single transaction during the next 90 days. I have transaction data for 7m customers, ...

Question 6

I'm trying to do a regression problem where I find Molar compositions of some chemical species. I'm using this kind of netwrok: ...

Question 7

I struggle to select the key features that contribute to PC1. I will use the public breast cancer dataset to illustrate the issue. Please feel free to point me to previous post if this question has ...

Question 8

I am working in a team developing a time series forecasting model using xgboost (or similar). We have a draft workflow for optimising model hyperparameters, incorporating an initial train-test split ...

Question 9

Need to make time series prediction on a large data set. There are both static and dynamic features. Static features like (store location id 10k+) and dynamics features like daily sales and daily ...

Question 10

I have built a knowledge graph with every customer having the same attributes, for example, gradeA, gradeB, gradeC. With this graph I want to attempt to find patterns between customers with shared ...

Question 11

Let's assume I have a column with float values (e.g., 3.12334354454, 5.75434331354, and so on). If I round these values to two decimal places (e.g., 3.12, 5.75), I think the advantages and ...

Question 12

When plotting a SHAP beeswarm plot on my binary classification model (predicting subscription renewal probability), one of the columns indicate that high feature values correlate with low SHAP values ...

Question 13

I'm building a neural network model to predict which student in a class will achieve the highest score on an upcoming exam (this is not the actual task, I actually modified the task to maintain ...

Question 14

In my regression-based machine learning project, I have features like coordinates (latitude and longitude) that I prefer not to scale or transform. The main reason is that reversing the transformation ...

Question 15

Given hourly updates of precipitation amount (for the preceding hour) and temperature, how would you calculate if it's slippery or not?

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Questions tagged [feature-engineering]

Approach to creating vector similarities between primitive voice sounds (i.e. basic consonants and vowels)?

How Do You Balance Feature Search Strategy and HP Optimization Cost?

LSTM feature scaling with windowing?

NLP of noisy unpredictable text to extract dates--just regex?

Is it best practice to remove outliers from transaction data used for training?

What does it mean when even a small set of samples don't give 0 loss?

Principal Data Analysis - how to determine the key features contribute to PC1 using scikit-learn python

Lagged feature engineering - time series forecasting with blocked cross validation

time series prediction with large number of static features

Feature engineering using Knowledge Graph

Rounding Float Values in ML Models

SHAP vs. Manual Analysis: Why Opposite Correlations for a feature?

How to Represent Structured Inputs in a Neural Network for Multi-Entity Prediction?

I didn't scale all features I used for prediction, does it make sense?

Calculating risk or amount of slipperiness based on historical weather data

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