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Questions tagged [feature-weighting]

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Multiple features test to see if 2 populations are similar?

I'm still a bit new to the world of statistics, so I apologize for the naivety of this question. I have three populations each with fifteen features, and I would like to determine if Population C is ...
Bre's user avatar
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Translate feature_importances_ to nontechnical stakeholders

Lets say nontechnical C-suite wants you to predict what the revenue would be for a certain customer base. And so you train a random forest model and it achieves high accuracy. You want to figure out ...
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What is the influence of transforming explanatory variables in regression? [closed]

Let's say I have a participant who performs a test and I am measuring EMG (multiple trials/epochs). This participant has to come in for multiple sessions and every time the EMG is measured. Now I want ...
Noah_Mandje's user avatar
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How to correctly create a new weighted feature column from 2 opposing features

I have the following dataset: Date ID 1 ID 2 ID1avg_rtg ID2avg_rtg ID1avg_Importance ID2avg_Importance 16/7/2022 1001 1000 1.21 1.68 23 68 In this dataset I have the average score of electric ...
Jason's user avatar
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Lowering the weight of particular features in a neural network?

Given sample data $x$, we hypothesize that some features (i.e. dimensions) of $x$ will generalize well, while others will generalize poorly. For example, when predicting medical diagnosis, age and ...
SRobertJames's user avatar
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127 views

Handling features which have the default value in most instances

I am using a Generalized Additive Model to predict a score between 0-100. One of the features in the model is a boolean value which is rarely true. When the value is true, it is a very strong signal ...
łówkèÿ's user avatar
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181 views

What are some optimal solutions when concatenating very high dimensional and low dimensional feature vectors?

I'm working on a problem where I need to concatenate feature from a resnet model and few extracted features for a end-to-end deep learning model. Model summary: ...
Zabir Al Nazi's user avatar
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How to make part of data entries more important for regression model

I am trying to fit polynomial ridge regression line for some datapoints. However I know that most of new data will be over the bounds of training data. Because of this fact I want to make part of the ...
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Determining index weights

I am currently creating a multiple variable index and tried using Principal Components Analysis to determine the weight of each variable. Specifically I'm using the ...
te time's user avatar
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1 answer
424 views

How to set feature engineering for day of a week?

Apologies if this is a very basic question. I'm currently learning data science and was wondering to help validating what I'm trying to do. So I have a model set up to predict event duration by ...
fokusfocus's user avatar
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Selecting Feature weights

I use the knn Classifier for a binary classification problem. To improve the classification results I would like to multiply features by weights that are learned from data. I found different ways to ...
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How to find significant predictors that can differentiate case and control without ML approach?

I have a dataset with more than 70 columns and I have an binary output column. What I did currently was to explore the dataset by plotting the bar and line graphs for the input variables vs output ...
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Accounting for Inter-Sample Collection Time Variability

I'm trying to run regression analysis on a dataset that features a pair of continuous variables that are collected at a certain time (in days). Whilst the data should be collected at a specific time, ...
Dan Adams's user avatar
1 vote
1 answer
165 views

Basic question about feature selection

I am new to machine learning. I have a basic question about feature selection. I have a dataset with 100 features which I used to regress an output Variable. When I do regression with all the ...
Peter Coggle's user avatar
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Different sample size of control and test groups

Hope someone can help my question: I have a survey study with one control group and one test group. Each is set to have 500 completes. However, we are short in sample in one group: Test is 350 and ...
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Model Based Feature Selection vs Wrapped Method Feature Selection

I read about Wrapped Method Feature Selection, I get that it is to look at the features then test them against the predictive model that we need then find if it has an effect or not and then decide to ...
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XGBoost and AdaBoostClassifier feature importances

I try to compare XGBoost and AdaBoostClassifier (from sklearn.ensemble) feature importances charts. From this answer: https://stats.stackexchange.com/a/324418/239354 I get know that ...
K4liber's user avatar
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1 answer
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On feature scaling and weighting for clustering

The issue of feature scaling and weighting for cluster formation has been widely discussed in several books and papers as well as several questions (e.g. here ). To my understanting, variable range is ...
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From unsupervised clustering to a weighted average?

I am in the process of writing my master's thesis, and have stumbled (as one often do..) upon an area of statistics that I am not familiar with. My setup is, that I initially have 2 features which I ...
Philip's user avatar
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2 votes
1 answer
98 views

Why wider range for a feature in Machine learning affects training?

I was reading through the Google Machine learning crash course and I can't digest the below point: If a feature set consists of multiple features, then feature scaling provides the following benefits:...
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How to weight features when doing text mining?

I have a case where I'm doing text mining over a list of product titles. In particular I want to run a clustering algorithm. But I also have some information about those products that I think can add ...
Franco Piccolo's user avatar
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2 answers
1k views

Number of principal components for PCA [closed]

Which criteria to consider while picking the number of principal components for PCA?
user213112's user avatar
5 votes
3 answers
4k views

How to describe most important features of ensemble model as list?

I have created 3 different models and output of them is a class probability in binary classification problem. Models are bit different, showing importance from different features. I have of course one ...
Analyst's user avatar
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2 votes
1 answer
673 views

Why does Feature Scaling work?

If I take a very basic example where my feature Matrix X is $$ \begin{matrix} 1 & 100 & 0.25\\ 1 & 110 & 0.5\\ 1 & 120 & 0.75\\ 1 & 130 & 1\\ 1 & 140 & 1.25\\ \...
Prashant's user avatar
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1 vote
1 answer
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Statistical method(s) to employ to find best features given a number of features [closed]

I am working on an anomaly detection application that uses keystroke dynamics. This is the pool of features that I have to my disposal: hold time = R(i) - P(i) key-up to key-down = P(i+1) - R(i) ...
TMK's user avatar
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1 answer
1k views

How to rank features based on an attribute in python? [closed]

I want to rank each attribute based on their ability to influence the dependent attribute(say for instance, "income" ) in the dataset. In R, I have used ...
user5717949's user avatar
1 vote
0 answers
49 views

How to reweight two datasets so they are the same by deleting members?

So my situation is that I have a large set of events, each of which contains many variables (e.g. mass, length, momentum, colour...). This set of events can be divided into two categorys according to ...
Clumsy cat's user avatar