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Questions tagged [feature-extraction]

Variables (used for prediction or explication) used in regression or regression-like models (like clustering, discrimination). Use this tag for questions about constructing such variables or selecting the best among them.

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extract features from parts of one image

I have several parts of one image that have one caption... I need to do image captioning by evaluating every part of the image to which the caption will belong so do I need to extract the features ...
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log mel energies

I want to convert mel spectogram to log mel energies what I used is ...
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Calculate features on stationary time-series data

I am trying to create a deep learning model that predicts the future price of crypto currencies based on past data. I downloaded the Open, High, Low, Close and Volume (OHLCV) data from yahoo finance ...
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extract features from low resolution

I have medical images and need to extract features from the layer before the classification layer using VGG for example but the ...
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For feature selection, do we use Chi-squared with Mutual Information together?

Or do we only choose one out of two for categorical data.
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Task of regression on graphs

Which tools are available to extract features from a graph. After that, I would like to perform regressions on those features. Initially, I was thinking about using the adjacency matrix of the graph. ...
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how to align sliding window to extract features from multi modal timeseries data?

I have two datasets that are collected at different frequencies at the same time. One is recorded at 128Hz and another one is recorded at 512 Hz. I am trying to extract some features using the moving ...
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Neural Network One-hot Feature concatenation

I'm trying to add features to a model with two one hot encoded features. The features are defined like this. ...
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Is Self-Supervised Learning a task of Representation Learning?

Maybe a weird question but: Currently, I'm writing a seminar paper about Self Supervised Learning for time series data. For this paper, I have to find methods to prepare unlabelled time series data ...
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do feature selection and model selection must share the same ratio between development set and test set?

As the title, after I performed a Feature Selection, is it mandatory to respect the same ratio (between development set and test set) in Model Selection?
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Methods for combining instance observations for classification

I am working on a project where I classify tiny moving particles into a few classes (fibers, hairs, glass shards, bubbles). The particles are only a few pixels large and are observed in a few frames ...
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2 answers
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Is it wise to always `StandardScaler()` features? [SOLVED]

My current investigations point to the sklearn.preprocessing.StandardScaler() not always being the right choice for certain types of feature extractions for neural ...
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NLP text representation techniques that preserve word order in sentence?

I see people are talking mostly about bag-of-words, td-idf and word embeddings. But these are at word levels. BoW and tf-idf fail to represent word orders, and word embeddings are not meant to ...
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How to detect features in a 3D point cloud with a simple neural network?

I have a question and hope that you can help me. I am looking for a simple algorithm to detect features from unstructured 3D data. These features can have holes and they are an important part of the ...
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Automatic feature extraction from EMG, autoencoder vs variational autoencoder?

Thanks for checking my question! From the EMG signals of Parkinon's patients, I want to extract rigidity and bradykinesia information. In order to do that, we need feature engineering. But, I would ...
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How should I handle time-duration-based columns in classification?

For example, say I am trying to predict whether I will win my next pickleball game. Some features I have are the number of hits, how much water I’ve drinken, etc, and the duration of the match. I’m ...
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What kind of features can I obtain from IP:Port data?

I have a dataset that consist of the fields below. IP_Version,id,IP_TTL,IP_Source,TCP_Source_PORT,IP_Dest,TCP_Dest_PORT,data_size,timestamp What kind of features ...
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Use VGG19 to extract features from single channel YCbCr image

I have a set of images in the YCbCr format. I took only the Y channel and will use them to train a super resolution network. I would like to use a loss function named perceptual loss, which involves ...
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Feature Selection for vector of targets, Y=(y1,...,yn)

If I have an output/target, y, that is a vector of targets, e.g. (y1(t), y2(t), y3(t), y4(t)) and training data X, also a vector, (x1(t),...,xn(t)), and I wish to do e.g. regression, neural nets, and ...
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Anomaly detection for varying dictionary

I want to detect the anomaly in the processes taking up the most CPU percent. I receive the data as a time series of dictionary values like so: ...
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Best way to represent a version feature based on percentiles

We're training a binary classifier in AutoML, and one of the features consist of browser versions. Currently these versions are provided "normalized" to the model, according to the ...
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What does re.split(r'[_]' , i) does? [closed]

What does re.split(r'[_]' , i) does? I have a function with the above code. Can someone please explain how does the split occurs.
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When an author says Features are the input to Machine Learning Model what does it mean?

I am reading an article about graph neural network and it is mentioned: In this step, we extract all newly update hidden states and create a final feature vector describing the whole graph. This ...
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Regarding pos tagging

I working on a dataset, I did the pos_tagging using nltk. Now I want to know which sequence of grammar is most common in my rows, then I want to define a chunk grammar based on a common grammar ...
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Approaches for multiclass classification with a reference level to extract variables of importance?

I have a dataset with with multiple classes (< 20) which I want to classify in reference to one of the classes.The final goal is to extract the variables of importance which are useful to ...
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Using Validation Set in Transfer Learning for Feature Extractor Preprocessor

I have a set of images of products. I am using transfer learning for images feature extraction in this way : I load a model (res-net, vgg) I add 2 dense layers, first one will be my features and the ...
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Class mismatch in categorical features after ordinal encoding and other feature inconsistencies between train and inference

This post is about three cases of feature mismatch, an issue that is quite prevalent and challenging in many production ML use cases. Let's suppose we have a new dataset on a weekly base which we ...
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sampling fall on which category of data mining

I have a question regrading the steps of data mining. After searched on Google I came to know that Data mining have 7 key steps ...
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Using SHAP values as features in a classification problem

I'm looking for feedback on a methodology I've tried that has yielded strange results. Problem background: supervised multi-class classification problem for which I've used a random forest to create ...
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What is the best way to limit number of features in TF-IDF?

I am using the tf-idf to build representations. It is large dataset and it quickly becomes too much for my RAM if I convert the matrix to a Data-Frame. What is the best way to reduce the number of ...
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How to cluster/group these data points (using K-Mean or Hirarachal clustering)

I have genes from different species Gene A , Gene B, Gene C, ... Gene Z Some Genes are similar to each other ...
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An efficient way to encode & embed tabular data of a video into a transformer?

So a little bit of a background: I have a folder which contains video files of lets say humans doing a certain action (i.e. walking) where each .2 seconds is documented in a ...
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Is Hough transform an appropriate line detector for my problem?

I try to get automated labels for images with the help of computer vision. Problem The labels are papyrus fibers on the outer edges of a papyrus fragment. After some research (for example [3]), I come ...
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Word classification

I have a task to classify the model of a product from its part number using machine learning. Part numbers can be of different lengths and forms and can contain both letters and numbers and also ...
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Feature creation: Problem with correlated features?

I recently started to read about feature creation. I've seen some general guidelines although I am not really sure if they are completely true, for example: 1 - Linear classifiers for binary ...
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Features of the fourier transform for machine learning

i intend to extract features from time-domain measurement data. I feed the features to machine learning algorithms to detect anomalies. In the time-domain, i extract mean, RMS, skew and standard ...
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Clustering features of a class based upon the difference between features of a reference class and the particular class across multiple datasets?

I want to separate (generalized separation) the features of several classes based on the difference between the features (floating point values) of the particular class and a reference class across 7 ...
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1 vote
1 answer
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Algorithms for casual feature selection for continuous Y

Currently I have been trying to find some good algorithms for feature selection. Using correlation or other non casual type of method will not be the right way to do a feature selection. I'm am ...
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Filters in subsequent layers

So I recently started learning about CNNs, and one question struck out to menthe filters used in the second layer are a combination of the filters used in the first layer, right? Lets say I make use ...
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Why do we use multiple convolutional layers, instead of a single layer

My intuition is that, when we have the raw pixels from the image, suppose we want to extract an eye, why don't we just try to use an eye detector to extract the eye feature from the image, why do we ...
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2 votes
1 answer
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Imputing Data that Isn't Missing

I have two columns, [Date Activated] and [Date Closed]. One is the date an account was activated, and the other column is the date an account is closed. There are three scenarios: Case 1 (1/6 data) ...
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How to get dummy variables from "first name"

I intend to predict the age of customers using some features. There are some categorical features that I need to convert to dummy variables before the modelling stage. Since the datasets are so big (...
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ResNet50 + Transformer

In many papers people extract features from image using ResNet and than pass them through transformer. I want to implement the same. I want to get features and than classify them using transformer. ...
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How should I engineer features for Named Entity Identification task?

I was working on Named Entity Identification (not recognition) task. In this NLP task, given a sentence, model has to predict whether each word (aka token) is named entity or not. The dataset used ...
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How many features should be there in a dataset to apply any feature selection method?

I am working on a time series, regression problem, where I have 10 features and 180 observations. I would like to understand what the minimum number of features should be in a dataset to use feature ...
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What is the difference between features in vgg

I read the architecture of the model but this is the first time I try to use it . The calculations of the features map will be different if I extract the features from the two last layers or from the ...
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Feature selection algorithm for psychometrics, when there is several predicted variables

I'm on a psychometric study. It is a survey. All variables are on a scale of 7. So these are considered as continuous variables. I have this dataset: 600 features 100 predicted variables 100 survey ...
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Extract features using Bounding Box

I have a ground truth bounding box for a 3d object. I would like to extract useful features for the object. My goal is to concatenate these visual object features with language features (from the ...
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How to load any particular folder files from a zip dataset

Twitter is a great source of information. Using The Health-News-Tweets.zip dataset contains tweets by different agencies like BBC Health, CBC Health, etc. I will ...
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Feature extraction with mixed categorical and numerical variables

I've been reading up on feature extraction methods - but the ones I have come across all seem to be numerical. To do feature extraction on a mixed numerical/ categorical dataset are there techniques ...
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