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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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How to choose Elastic-Net parameters for feature selection?

I recently came across using elastic nets for feature selection which brings in regularization to temper the sparsity properties of L1 regressions. I would like to learn how to use elastic nets for ...
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feature weighting and feature subset selection

I'm planning to work on feature selection and am looking for some useful documentations, tutorials, books or anything about this topic and especially about feature weighting. Thank you for your help!
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3answers
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How to find the most important attribute for each class

I have a dataset with 28 attributes and 7 class values. I want to know if its possible to find out the most important attribute(s) for deciding the class value, for each class. For example an answer ...
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1answer
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Which order is correct Feature Selection then Outlier Detection or vice versa?

which of these orders is correct? First (Feature Selection) Second (Outlier Detection) or First (Outlier Detection) Second (Feature Selection)
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Looking for freely available labelled time series data sets for automated feature extraction and selection

I am looking for recommendations of big, labelled time series datasets that are freely available on the net. My aim is to apply and evaluate methods of automatic feature generation and selection, ...
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Feature selection, hyperparameters tuning and model test with Cross Validation

I don't know if this is a valid question, but I am not finding any documentation or explanation anywhere and I have a doubt. I have a dataset - 100 samples, 50 variables, 3 response variables (1 ...
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1answer
40 views

how to build a predictive model without training data neither historical data

I m trying to score "how much a product is expected in the market". I created some features: How much this product is used each year. Where was it used . how many product for each country. the main ...
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1answer
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Classifying objects based of a varying number of the same type of feature vector for each object

For a congressional session, I have created a doc2vec model of speeches made. Using the vectors from this model, I have a dataset of each congressperson, their political affiliation, and a list of the ...
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Perform Pearson's correlation and chi-squared test for feature selection in a dataset with a mixed type of features

I've a dataset of about 200 features and 5000 instances. These features comprise of different data types like percent (string like 4.50%), dollar amount (value between $0 - $1,000,000), discrete ...
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Test and compare Model Performance

I have a 93 x 41 data frame in r, with three response variables, one numerical, one binomial and one multinomial. I'm employing various feature reduction methods (VIF, PCA, PCA+ICA, Relief) and ...
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Reduce number of vectors in dataset to achieve the “same average dimensions result”?

I have many tests (rows), each with a large set of 3D vectors (features/cols). Each vector complies: Xn + Yn + Zn = 1 Simply averaging all components ...
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Discard overlapping data sets in classifications

I think I have overlapping in the training data sets. Because if I use the training set that of one label as the test documents, it will output other labels as classifications. I'm thinking of ...
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Does it exist feature selection/reduction techniques in $O(n \cdot d)$?

I'm curious to know if feature selection and/or feature reduction techniques exist, which are linear on number of data $n$ and on number of dimensions $d$. References and source code are very welcome....
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Feature Importance Python

My dataset has around 1000 features and 30k rows. All the feautres have value either 1 or 0. My target variable is Size which 3 classes : Small, Medium and Large. I have around 5k "small" data ...
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Suggestions on using model in production 1 test at a time

I have created an Artificial Neural Network with 4 categorical features and a binary outcome either 1 for suspicious or 0 for non-suspicious: ...
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0answers
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Quantifying feature importances using Auto-encoders

I have a set of features(mixture of numerical and categorical), each of size n. I am embedding them into a dense lower dimensionality space using an auto-encoder. I want to know if it is possible to ...
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1answer
23 views

Select more or less features if results are almost the same

I am having a dataset of 3500 observations with 70 features each with binary labels/targets for classifications purposes. My aim is to score more than 90% precision and the highest recall possible ...
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Serial Clustering of features

Let's say we have two categorical features A, B for N samples. Is it okay if we do say ...
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2answers
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Help with creating dimensions/features

It is quite hard to name the title properly as I just started to learn ML, will try to explain here. I want to practice ML by creating Movie suggestion algorithm. I came up with the following list of ...
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3answers
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In machine learning how to find feature interdepencies? [closed]

Given a data set of N features, wherein some the features in this set were derived from other features from the same set, I am trying to discover inter dependencies between features (something like ...
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1answer
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Feature importance ratio

I trained a Random Forest classifier (sklearn) and consequently computed the feature importance and consequently ranked them. The forest has 100 estimators. My top 5 features with their importances ...
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2answers
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In natural language processing, why each feature requires an extra dimension?

I am reading Machine Learning by Example. I am trying to understand natural language processing. The book used Scikit-learn's fetch_20newsgroups data as an example. The book mentioned that the text ...
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Best way to determine the number of features for RFE

I am applying the feature selection method, RFE (recursive feature elimination), from scikit-learn to a dataset. I do not have any pre-determined number of features for RFE and would rather get the ...
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0answers
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Metrics to evaluate features' importance in classification problem (with random forest)

I want to evaluate the importance of each of the features of a 2000x60 dataset in a classification problem with random forest. The most widely used ones apparrently are: Cross Entropy-Information ...
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1answer
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Metrics/Methods for deciding duration of video retention for on-demand websites

This might be a general question but I thought this might be the best place to brainstorm. If I had a video website that only wants to retain videos on-demand for a certain number of days before ...
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Detect multicollinearity in real-life, non-normally distributed data

I am currently trying to figure out whether my data (consisting of thousands of rows, some is numerical, and some are categorical, and some are ordinal) has multicollinearities or not. One thing I ...
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Assigning scalar values for PID for order in Neural Network

I have built a neural network using Windows Process's I started off with only two features, the file path with parent process, and the file path with child process. I am slowly adding features for ...
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Representing a community as a vector

My setup is this: Suppose I have transactional data over a large period of time. The parties of each transaction are labled, and I use Louvain algorithm for detecting communities (and sub-communities)...
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Combining features for explainable binary classification, imbalanced dataset with minimal manual checks

I'm building a binary classifier which should detect between "fake" and "genuine" objects for a certain domain. I have designed a dozen of numerical features which are typically large for fake objects,...
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1answer
17 views

Using historical label as a feature in my ML model?

I am working on a predictive model to predict change in the price of an asset (up, down, no change). The labeling is based on the derivative of the price and is exponentially smoothed with an alpha of ...
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1answer
34 views

Optimising Expensive Functions

I'm trying some different techniques to optimise a Boosted Gradient Regressor by using an evolutionary programming technique to try and find the most efficient set of features. So far I've been having ...
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1answer
285 views

How to implement feature selection for categorical variables (especially with many categories)?

I've been trying to get some ideas of how I could treat categorical variables when doing feature selection. Mainly I've been running Random Forest feature importance on Python for which preprocessing ...
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1answer
28 views

Feature selection for time series prediction

I'm working on an LSTM-based stock market forecasting problem and trying to figure out a way to select input variables. When calculating correlation between variables (e.g. Close price of Tesla vs ...
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15 views

Relief Algorithm misses relevant feature?

I have a generated a set of imbalanced data: 70 samples of class 1 and 1000 samples of class 2. The target variable and all predictors are boolean. I've made two predictors that should be relevant to ...
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0answers
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How to classify a dataset into 5 classes even though the performance is low?

I have a dataset of 5 classes with 8 features, say A, B, C, D and E. Now when I try to classify these into individual classes, I get accuracy, specificity and sensitivity of approx 50-60%, which is ...
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When to remove correlated variables

Can somebody please suggest what is the correct stage to remove correlated variables before feature engineering or after feature engineering ?
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1answer
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Best practices for selecting categorical features

I'm trying to create a classifier that will predict whether someone will attend an interview or not. Each data point is for a single candidate and contains details such as the location of the ...
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How to understand when partial dependence plot and feature importance don't agree

I'm checking partial dependence plot and feature importance on my binary classification using gradient boosting. The top feature based on the feature importance is a flat line at partial dependence ...
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1answer
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the error occurred while selecting feature using recursive feature elimination in sklearn

I tried to rank the feature using recursive feature elimination in sklearn. However, I got this error when using RFE. here are the error and code information. ...
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2answers
26 views

how to represent location-code as a feature in machine learning model?

I am trying to predict the damage to a buildings after earthquake on a dataset which contains "district number" as feature. I think the feature will have a significant importance in predicting the ...
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2answers
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Text representation using TFIDF .toarray() freezes my computer. Too many features to handle?

I'm new to Data Science, so hopefully this question makes sense. I have a dataset with ~50,000 rows. It consists of one column that has item category in it and one column with item description in it....
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35 views

How to do feature engineering for email cleaning / text extraction?

I have a large batch of email data that I want to analyse. In order to do that, I need to first prepare the data, as the messages are quite often >80% noise. Generally speaking, my dataset's structure ...
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Samples that share same features but have different labels/output values

I have built a clustering model based on numerical data, specifically time series clustering. Let's say using sales quantities (over time) of different products. In other words identify different ...
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2answers
134 views

Testing independence of random variables in Python

Are there any tools available in Python that allow for testing of independence of two random variables (data columns)? I have two columns of data $X$ and $Y$. They can be both discrete, with values $\{...
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1answer
16 views

automatic feature selection

I have a lot (thousands are possible) of automatically-generated ordinal features that i'd like to exploit , to differentiate between two classes. I'm looking for some measure that will select the ...
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0answers
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Feature importance over a subset of instance space instead of an entire instance space

I'm really curious if anyone has faced this problem before, or is it even widely studied at all. Imagine we have a feature that isn't important (based on many widely available and textbook feature ...
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2answers
35 views

What to do if my target variable is column of lists? [closed]

How I can transform my target variable(Y)? As it is list, I cann`t use it for fitting model, because I must use integers for fitting.
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Activity Detection

I am attempting to classify every point in a sound file as either being active or inactive. I have a binary mask of my training data which represents when they are active or not. Not every sound file ...
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1answer
41 views

Feature selection

Is it possible that out of several attributes $p$, only one attribute could be selected by a model in the feature selection and training phase? Then basically we are fitting a line. Basically, I was ...
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0answers
306 views

Isolation Forest Feature Importance

As of scikit-learn version 0.19.1, there is no implementation for calculating feature importance in an Isolation Forest. I'm also having trouble finding any online resources proposing ways to get at ...