Questions tagged [feature-selection]

For questions related to the concept of feature selection (also known as variable selection or attribute selection), which is the process of selecting a subset of relevant features (a.k.a. variables or predictors) for use in model construction.

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19 views

Selecting features for a neural network: is it redundant to have a feature that is an average (or max, or min) of some other features

I'm trying to create a neural network that would able to look at the current price of a crypto asset and classify between a "BUY", "SELL" or "HOLD". So far for my input ...
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79 views

How can I select features for a symbolic regression problem to be solved with genetic programming?

I want to solve a symbolic regression problem with genetic programming. My dataset is similar to this one, but I have 30 features, and I want to use only the most sensitive features. I found this ...
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13 views

Is there a theoretical or recommended number of estimators for Random Forest in Feature Selection?

I am using a RandomForestRegressor as an estimator in the SelectFromModel object (sklearn) ...
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64 views

How to predict the best from a set of messages - best practice

Suppose I have a set of messages A,B,C,D and I want to produce the best message for a website user at a given time. For training I plan to show random users a random single message [A/B/C/D] and fill ...
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In the Binary Flower Pollination Algorithm (using the sigmoid function), is it possible that no feature is selected?

I'm trying to use the Binary Flower Pollination Algorithm (BFPA) for feature selection. In the BFPA, the sigmoid function is used to compute a binary vector that represents whether a feature is ...
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37 views

How does uniform offset tiling work with function approximation?

I get the fundamental idea of how tilings work, but, in Barton and Sutton's book, Reinforcement Learning: An Introduction (2nd edition), a diagram, on page 219 (figure 9.11), showing the variations of ...
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44 views

What is the impact of the number of features on the prediction power of a neural network?

What is the impact of the number of features on the prediction power of an ANN model (in general)? Does an increase in the number of features mean a more powerful prediction model (for approximation ...
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71 views

Does the order in which the features are concatenated to create the state (or observation) matter?

I'm experimenting with an RL agent that interacts with the following environment. The learning algorithm is double DQN. The neural network represents the function from state to action. It's build with ...
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48 views

Is automated feature engineering a path to general AI?

I recently came across the featuretools package, which facilitates automated feature engineering. Here's an explanation of the package: https://towardsdatascience....
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23 views

What is the best way to do classification using both text and numerical data?

For my BSc thesis I am trying to classify asset price direction (up/down/neutral) using numerical features and Swedish text. The text is short financial news (ca 50 words each) that have sentiment ...
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78 views

Why does the training time of SVMs dramatically decrease after applying dimensionality reduction to the features?

Training an SVM with an RBF kernel model with c = 5.5 and gamma = 1.06, for a 5-class classification problem on the NSL-KDD ...
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31 views

When adding a feature is useless?

"simple" issue: I'm building a model, where from a feature set A I want to predict a target set C; I need to understand if another feature set B, together with A, can improve my model ...
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28 views

How to obtain SHAP values

I want to obtain SHAP values with kernel SHAP without using python but I don't really understand the algorithm. If I have a kNN classifier, do I have to run the classifier for all the coalitions ...
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22 views

Visualisation for Features to Predict Timeseries Data

I have a course assignment to use an LSTM to predict the movement directions of stock prices. One of the things I am asked to do is provide a visualization to compare the predictive powers of a set of ...
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22 views

How can Cat Swarm Algorithm (CSO) used for feature selection?

Cat swarm optimization (CSO) is a novel metaheuristic for evolutionary optimization algorithms based on swarm intelligence which proposed in 2006. See Feature Selection of Support Vector Machine Based ...
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19 views

Feature extraction for exponentially damped signals

I am looking into exponentially damped signals where it is a stationary signal (after implementing the Adfuller statistical test) and I would like to look into how can I extract meaningful features ...
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53 views

What are examples of commonly used feature and readout maps?

It is well-known that deep feedforward networks can approximate any continuous function from $\mathbb{R}^k$ to $\mathbb{R}^l$, (uniformly on compacts). However, in practice feature maps are ...
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2answers
85 views

How should I select the features for predicting diseases (in particular when patients specify their health issues)?

My aim is to train a model for predicting diseases. Now, according to this Wikipedia article, diseases are classified based on the following criteria in general: Causes (of the disease) Pathogenesis (...
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29 views

Binarize ConvNet Feature vector [closed]

Given a pre-trained CNN model, I extract feature vector of 3450 reference images FV_R as follows: ...
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1answer
168 views

What is the $\ell_{2, 1}$ norm?

I'm reading this paper and it says: In this paper, we present a multi-class embedded feature selection method called as sparse optimal scoring with adjustment (SOSA), which is capable of addressing ...
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37 views

Interpretability of feature weights from Gaussian process classifier

Suppose I trained a Gaussian process classifier with a linear kernel (using GPML toolbox) and got some feature weights for each input feature. My question is then: Does it/When does it make sense ...
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1answer
178 views

How does the decision tree implicitly do feature selection?

I was talking with an ex-fellow worker and he told me that the decision tree implicitly applies a feature selection. He told me that the most important feature is higher in the tree because of the ...
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1answer
25 views

Should I use my redundant feature as an auxiliary output or as another input feature?

For example, given a face image, and you want to predict the gender. You also have age information for each person, should you feed the age information as input or should you use it as auxiliary ...
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3answers
108 views

Can neural networks be used to find features importance?

I am wondering if I can use neural networks to find features importances in similar manner as it can be done for random forests or decision trees and if so, how to do it? I would like to use it on ...
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19 views

How to combine features with different temporal scale in machine learning

We have various types of data features with different temporal scale. For example, some of them describe the state per second while others may describe the state per day or per month from another ...
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82 views

Feature Selection using Monte Carlo Tree Search

I'm trying to tackle the problem of feature selection as an RL problem, inspired by the paper Feature Selection as a One-Player Game. I know Monte-Carlo tree search (MCTS) is hardly RL. So, I used ...
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2answers
32 views

What features should a dataset to predict monthly retail sales for a motorcycle spare parts shop have?

I am making an AI model to predict monthly retail sales of a motor cycle spare parts shop, for that to be possible I have to first create a dataset. The problem I am facing is what features should the ...
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2answers
57 views

How to analyze data before going for machine learning training?

For example, I have the following csv: training.csv I want to know how I can determine which column will be the best feature for getting the output prediction before I go for machine training. Please ...
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1answer
68 views

Feature selection of an acoustic voice dataset for classification

I'm trying to gain some insight into acoustic voice data composed of 19 features. I want to understand what features contribute most for classification. ADDED: Most features are related with the ...
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1answer
86 views

When should I use feature learning as opposed to feature engineering?

With the advancement of deep learning and a few others automated features learning techniques, manual feature engineering started becoming obsolete. Any suggestion on when to use manual feature ...
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2answers
51 views

Problem extracting features from convolutional layer where the dimensions are big for feature maps

I have trained a convolutional neural network on images to detect emotions. Now I need to use the same network to extract features from the images and use them to train an LSTM. The problem is: the ...
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3answers
129 views

How much can the addition of new features improve the performance?

How much can the addition of new features improve the performance of the model during the optimization process? Let's say I have a total of 10 features. Suppose I start the optimisation process using ...
3
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1answer
114 views

What is a good descriptor for similar objects?

I am developing an image search engine. The engine is meant to retrieve wrist watches based on the input of the user. I am using SIFT descriptors to index the elements in the database and applying ...
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2answers
70 views

How to recognize non-circular radial symmetry in images?

This is a question about pattern recognition and feature extraction. I am familiar with Hough transforms, the Fast Radial Transform and variants (e.g., GFRS), but these highlight circles, spheres, ...
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2answers
76 views

How can I minimize the number of answers that are relevant to a machine learning model?

Problem: We have a fairly big database that is built up by our own users. The way this data is entered is by asking the users 30ish questions that all have around 12 answers (x, a, A, B, C, ..., H). ...
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1answer
648 views

How come that the addition of features can decrease the performance of a neural network?

I have a Remaining Useful Life (RUL) prediction problem that I want to solve. When I added two or more features as inputs to my ANN, the accuracy of my ANN has been decreased. More precisely, I've ...
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4answers
236 views

How do I select the relevant features of the data?

Recently I was working on a problem to do some cost analysis of my expenditure for some particular resource. I usually make some manual decisions from the analysis and plan accordingly. I have a big ...