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Questions tagged [feature-selection]

Methods and principles of selecting a subset of attributes for use in further modelling

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integration of Feature Selection in Pipeline

I have noticed integrating feature selection in a pipeline alters results. Pipeline 1 gives slightly different results with pipeline 2. Why should this be so? Pipeline 2 ...
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ML feature selection pipeline advice for high dimensionality binary classification problem (UFC WINNER preds!)

I am looking for some advice on how I can improve my predictive accuracy on a binary classification problem for betting on UFC (i.e., predict whether Fighter1 (usually the favorite, or Fighter2 (...
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Unique Feature Selection's for customers using Azure ML Studio

I have this weird kind of requirement that i need for my azure ml model, not sure how to make it, so its that i will provide the model a bunch of data and in that data each row signifies a single ...
Siddhant Chimankar's user avatar
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When using Chi-Squrare test in feature selection makes sense?

What are the prerequisites that need to be fulfilled before conducting a chi-square test (Bivariate analysis)? For instance, before having a correlation matrix, we should first ensure linearity. What ...
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how to deal if input feature are all categorical but target feature is discrete numerical, it is giving exact numerical for known data

the following data is to detect malnutrition among children under age 5 and the value_r is the percentage estimate of wasting among the population. should I apply the decision tree as an entirely ...
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Feature Selection - determining the significance of imbalanced categorical data column

I have a dataset with a categorical column that contains three categories. One of the categories represents 98% of the data, while the remaining 2% are distributed between the other two categories, ...
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Effect of removing duplicate and identical entries on dimensionality reduction

I have huge data with thousands of observations and millions of features. I need to do clustering so I use PCA/t-SNE/UMAP for dimensionality reduction followed by K-Means. Currently, I retain only ...
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Clustering task: drop or not drop a categorical attribute/feature for which each row in the dataset contains a different value

I am dealing with a clustering task. In the dataset I am using there is a categorical feature and for each row in the dataset I have a different value for that feature (my dataset consists of 1000 ...
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How to implement Ant Lion Optimization (ALO) feature selection for KNN Classification Problems?

I have been assigned for a project related to text data classification, i have preprocess and vectorized the data with TF-IDF. For feature selection i am using pyMetahueristic library to implement ALO ...
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RFECV giving same test scores for every feature size

I am trying to reduce the feature space of my training dataset down from the 16000 it currently is before engaging in Random Forest Classification. Initially I removed all features in less that 5% of ...
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How to handle using input feature (clicks) when it is used in target too?

I am trying to create a ranking model, where I am thinking about creating ground truth based on clicks by user. But at same time past clicks made by users seems like a vital input feature too. Any ...
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Different Algorithms for 50-50 A/B Testing

We are running A/B tests on web app customers, given a customerId. Each customer will see different web-feature designs. Trying to prevent usage of Feature Flags as its not currently setup yet in our ...
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Different patterns in dataset

Suppose some features in a dataset have a linear correlation with the target variable, some have a polynomial correlation, and for categorical features, the target values tend to distribute ...
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Testing accuracy is higher than training accuracy

My testing accuracy is way higher than my training accuracy. I have used feature selection and split the data into training, validation and test sets. ...
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If my target variable is binary, is it better to use Pearson's or Spearman's for my correlation vector?

I'm using a corr vector, combined with RFE, to perform feature selection. I keep reading conflicting things online as to whether I should use Pearson's or Spearman's...
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Chi-Sqare test and Continuous values

How does chi-square test work for continuous variables. I see that it is used in most papers to test dependencies between continuous explanatory variables and the target variable. Please how does this ...
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How to treat single column with both continuous and categorical data for ML model

I am working on financial data where I have a feature(column) with 90% values between 0-1000 (continuous) and 10% values as -1, -2 and -9. (default values) Default value definition: -1: data not ...
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important feature selection using dimensionality reduction algorithms

I have a dataset having more than 25000 features. I did perform noise removal using the histogram approach, and this dataset gets reduced to more than 5000 features. There are two classes, healthy and ...
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Feature engineering for interest-based age classification

I have a dataset which has users (rows) with the list of their interests (IABs), which looks like this ...
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Using time serie to predict another variable

I would like to analyse head rotation data in space. For this I measured at 15HZ the rotation around the X, Y and Z angles for a little more than ten minutes. I would like to use these movements to ...
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Classification Algorithms for Geospatial Vector Data

I am new to the world of Geospatial Analysis. As such, I am interested in Machine Learning / Deep Learning techniques for classifying geospatial vector data specifically (as opposed to raster data). I'...
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Having problems replicating the results of a series of N LASSOs fit to N datasets in R

I have fit n LASSO Regressions on n different data sets (the 'datasets' object is an R list of length n where each element is a data.table which is a light and fast data frame from the data.table ...
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Can using the mean of absolute Shapely Values for feature importance give very wrong results?

In a classification problem, suppose a model has 2 variables, A and B, and the null model (the model without any variable) predicts 50% probability for belonging to class 1 for all the instances. Now ...
Amir Jalilifard's user avatar
1 vote
1 answer
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Why the marginal contribution of a feature is the difference between the feature effect minus the average effect

In several sources the marginal contribution is defined as the difference between the prediction with and without the feature. However, recently I read an article where the marginal contribution was ...
Amir Jalilifard's user avatar
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Best package and function in R to use to replicate my (Backward & Forward) Stepwise Regression results I got using step from the stat package

I am doing a research project as a 2nd author on a paper exploring the properties of a novel algorithm for Optimal Variable Selection where I am running the benchmark Variable Selection Methods. Each ...
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How recursive feature elimination with cross validation internally works?

I am trying to understand how recursive feature elimination with cross validation works (the RFECV on sklearn). Lets say that we have 10 features, and we perform <...
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Does sklearn perform feature selection within cross validation?

I would like to add a feature selector on my pipeline and use gridsearchcv to tune both the hyperparameters of the selector and the classifier(s). I am wondering if sklearn performs feature selection ...
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Training a Model that Doesn't Always Have All the Features

I am creating a model that gathers data from multiple sources and determines a confidence level for an instance that is common across those sources (ie. all sources have different features, but all ...
Andrew Davis's user avatar
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Why the order of the fearures affects synapse LightGBM predictions?

I am using LighGBM Classifier and Regressor and it seems that the order of the features I am adding, affect the predictions of the model. Everytime I change the order, another result comes up and with ...
Chrysa Rinou's user avatar
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Which Feature Selection Techniques for NLP is this represent

I have a dataset that came from NLP for technical documents my dataset has 60,000 records There are 30,000 features in the dataset and the value is the number of repetitions that word/feature appeared ...
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Would adding Elastic Net as an additional Benchmark add any value when LASSO is already an included benchmark?

I am currently engaged in a research project with a collaborator in which he is proposing a novel learning algorithm for optimal variable selection, and exploring its computational, statistical, and ...
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Quantifying the performance of Stepwise Regression ran on Monte Carlo generated datasets & comparing them to your method of interest

The source data files and scripts referenced here and from whom lines of code are included here can be found in my GitHub Repository for this collaborative research project exploring the properties of ...
Marlen's user avatar
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A good 4th Benchmark method to compare the performance of a novel Variable Selection Algorithm being evaluated

I am collaborating on a research project with a respected econometrician as a graduate student (although only in an MS program, not PhD program mind you) exploring the properties and comparing the ...
Marlen's user avatar
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Determine how each element in a vector contributes to cosine similarity when compare with other vector

I have a vector that represents my object and does a job of calculating which object is similar to the other object by using cosine similarity. To create that vector, I've combined many features that ...
Can Nguyen's user avatar
6 votes
1 answer
262 views

Logistic Regression Modeling & Interpretation [closed]

I'm building a logistic regression model to predict the credit risk of lending company customers. I'm using dataset from kaggle : https://www.kaggle.com/datasets/ranadeep/credit-risk-dataset/code ...
Jovian Aditya's user avatar
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Redundant feature after one hot encoding

I have a numerical feature called $x$ and a categorical feature called $y$. $y$ is an ordinal feature (A,B,C,D,E,F). I am using label encoding for my y feature and when I am seeing the correlation ...
Jovian Aditya's user avatar
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101 views

HalvingGridSearchCV

Is there a way to get Feature importance from sklearn`s HalvingGridSearchCV? For example: Is there any way to access the feature importance? Please help me up. Thanks!
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Machine learning with mixed variables dataset (numerical, categorical and embeddings)

I'm working on a machine learning project where I'm trying to predict the revenue of a movie. My dataset contains mixed data types. There are numerical features (rating, number of votes, release year,....
Mathieu Rousseau's user avatar
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1 answer
112 views

Should I use "Recency" as an predictor for churn if I want to catch churners early?

I want to build a customer churn prediction model that predicts probability of churn the next day and I'm looking for some features that might be important for the target variable which has outcomes ...
Parseval's user avatar
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Variable selection and NA

I have a very large dataset with a lot of NAs in the data. I want to perform an analysis and have to select the variables that are of most interest. I feel like I have to take 3 steps before I can ...
Wilko's user avatar
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what are the solutions for efficient feature selection in a very large feature space?

I have a classification dataset (50k observations and 10 features) on which I can't get a good result.. I want to try increasing the number of features.. I plan to automatically generate many feature ...
mr.T's user avatar
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Dealing with categorical columns with unbalanced value count

I'm doing some data processing and wondering what is the best practice for dealing with categorical columns that has a value counts plot looking like the below (these are one-hot-encoded at a later ...
fendrbud's user avatar
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Can/should a logical multi-class classification anomaly detection system be described as "unsupervised machine learning"?

I would like to ensure that my use of terminology is accurate. My question is: what terminology should I be using in this case? The system I am building assigns classes (-1, 0, +1) to observations ...
HackJob99's user avatar
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Feature Engineering/FS

I've a dataset which consists of 33 features. Out of which first 32 features are latitude & longitude positions for 16 machines at 16 different locations (16latitude & 16 longitude values). ...
user125193's user avatar
1 vote
1 answer
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Why does feature selection matter if your model has L1 regularization?

I've been tinkering around with boosted trees, and I saw that for common libraries there is a parameter you can set to determine L1 regularization. I doubled my original feature set to around 130 ...
ron burgundy's user avatar
-1 votes
1 answer
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Machine learning feature selection

I have 40 Independent variables in dataframe. Out of these 40 IV's 6 IV's are as follows, X1 X2 X3 X4 X5 X6 Target 1 2 3 4 5 6 21 2 4 1 3 5 4 19 As seen in above table, target variable value is a ...
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Trying to find a Model for multiclass classification problem where you want two classes close together but far away from a third?

So I've got this problem where I want to find out where two classes are more a like ( features wise) than a third. So for example if I have three classes {A,B,C} I want to find out where class A and B ...
Steven Wijnen's user avatar
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1 answer
542 views

How does SelectFromModel from scikit-learn select features?

When I use XGBClassifier with SelectFromModel the algorithm always returns around five features regardless of the ...
Niyaz's user avatar
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What would be a good method for detecting symbols in an image and finding those elsewhere?

I'm trying to build a system that can detect symbols from a legend image, then find and count those symbols in a diagram For example the legend would have symbols like this, with a label next to them ...
Jacob Pradels's user avatar
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Which redundant feature should be use

I have two redundant features. A & B with 0.85 correlation. I know only one of them should be used to trained my model, but which feature should i use? A or B? Is there any method that can i use ...
Jovian Aditya's user avatar

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