Questions tagged [feature-selection]

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

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32 views

“help” decision tree by tying 2 features together

Assuming I have in my dataset 2 (or more) features that are for sure linked (for example: feature B indicates the amount of relevance of feature A), is there a way I could design a decision tree that ...
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1answer
93 views

Mapping between original feature space and an interpretable feature space

I'm reading the following really interesting paper https://arxiv.org/pdf/1602.04938.pdf on local interpretable model explanations on page 3 however particularly section 3.3 Sampling for Local ...
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174 views

Feature Selection: Having a large number of features select those features that classify the target class best

I have time series data and I'm using the cesium package to extract several features. Now the thing is, the number of extracted features is pretty significant. I have tried various visualizations to ...
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1answer
480 views

Setting attribute weights in Weka

I'm working on feature weighting techniques (chi-square, relief..) for classification tasks using Weka. Can I add these weights to the dataset's attributes? If yes, how? Do the classification ...
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4answers
615 views

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
392 views

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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1answer
88 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
27 views

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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0answers
114 views

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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0answers
28 views

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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19 views

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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87 views

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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23 views

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
124 views

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
31 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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2answers
46 views

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
43 views

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
58 views

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
54 views

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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2answers
1k views

Best way to determine the number of features for RFE (recursive feature elimination)

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
244 views

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
17 views

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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0answers
98 views

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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0answers
18 views

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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0answers
89 views

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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1answer
37 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
78 views

Optimizing 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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2answers
4k 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
74 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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0answers
28 views

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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5answers
4k views

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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3answers
464 views

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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1answer
77 views

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
101 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
238 views

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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0answers
90 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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2answers
2k 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
33 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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1answer
90 views

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
69 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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1answer
67 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
2k 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 ...
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1answer
13k views

Number of features of the model must match the input. Model n_features is `N` and input n_features is `X`.

I am new to data science and trying get some results. I'm applying Decision Tree Classifier. When my train and test datasets' size are not equal I get an error `...
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0answers
76 views

When to perform feature selection, how, and how does data affect choosing the predictive model?

Some background: I am attempting to predict attendance at this place using various features I have collected. I added to these features by extracting binary information from some of them. For example,...
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2answers
165 views

Random Forests with complementary features

In my dataset, I have 2 features that are not only correlated but that makes sense only in the presence of each other. For instance, one would be the number of times a task was attempted and the other ...
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1answer
420 views

Interpreting lasso logistic regression feature coefficients in multiclass problem

I have a dataset with a large number of text features, where the target variable has three classes. I have encoded the features using tf-idf. This has resulted in a dataset with an extremely large ...
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1answer
177 views

Should I eliminate all ID columns and similar columns from training data? [closed]

This is a basic question so bear my ignorance. I feel like they contribute collectively in no way to the target. This is for performance and accuracy. The target is polar (0,1).
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3answers
10k views

Using python and machine learning to extract information from an invoice? Inital dataset? [closed]

DISCLAIMER: I have absolutely no background with machine learning/data science, and am unfamiliar with the general lingo of data science, so please bear with me. I'm trying to make a machine learning ...
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2answers
82 views

Number of rows vs. number of variables

I am new to the ML/DS field. I started a project where I need to predict the age of users. I'd like to build two models, one predicting the age group (I created 6 age groups), and the other one ...
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1answer
89 views

What's the best way to select features independent of the model being used?

I am using tensorflow's DNNRegressor to model a multivariate regression problem. I want to form an optimal feature subset from a mixed bag of categorical and continuous features. What would be the ...