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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propper feature encoding
I working with the following data set
also here is it's detailed description of "packet_dat" column
I can't understand how I can encode packet_dat column into proper feature so my ...
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Combining Computer Vision and traditional machine learning to predict respondent reactions (from a survey) to seeing a picture. Is it possible?
I have the following task Computer Vision/prediction task which I’m interested in hearing whether you guys think is feasible.
I have a dataset of 1000 respondents coming from a survey, where ...
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Encoding soft clustering results as features
I want to use cluster numbers from soft clustering algorithm output as a some sort of categorical feature (or features), add them to other features for further training in another model (Y's from soft ...
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How to build a categorization system without a target variable?
The data
I have a large dataset containing execution logs from various tests conducted over several years. The logs can be noisy and often contain a plethora of messages detailing the ongoing ...
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Feature selection for propensity model
I'm trying to build a propensity model for whether or not a customer will buy a second product. I was given data that looks like this:
| Age | Income | DaysSince1stPurchase | Bought2ndProduct |
|:---- ...
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How to represent facial features from video and classify high/low personality traits from facial features?
The dataset has 3-minute 30fps video conversations (no audio) of 150 extroverted and 150 introverted individuals. The goal is to classify them as "introverts" or "extroverts" based ...
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Why is the feature direction chosen in the direction associated with largest eigenvalue of $Σ_T$ in case of more than two classes?
Why is the feature direction chosen in the direction associated with largest eigenvalue of $Σ_T$ in case of more than two classes? Please see the following.
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Approaches to dataset, whose elements have different size
I am working with a dataset where each elements is a square table of size m-by-n, where m (the number of rows) is the same for all the data points, while n (the number of columns) varies from tens to ...
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How to train model with data received from different 3x accelerometers sensors?
I want to make a model based on accelerometer data to recognise different activities like running, walking etc. I have a small dataset collected from my target sensor. I found another dataset with ...
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How to analyze social media data to see its impact on a game's sales
I work for a console gaming giant. We forecasted the sales for a RPG game that was to be released few months back. But the actual sales was twice the forecast. This compelled the developers to ...
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Text classification with very short strings
I have a dataset of short job titles (e.g., 'marketing manager', 'system administrator', etc.) and their respective Census occupation code (e.g., 1006 Computer systems analysts). I am interested in ...
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How to Data Engineer a dataset to get the best featurres to predict a target class?
In my dataset, I have data of IDs that don't create any meaningful relationship with each other and when I test that dataset on different models I am not getting accuracy more than 40%.
Anyone can ...
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Sentiment extraction with hugging face ready to use model
I have a set of reviews for which I need to extract their sentiments and use those sentiments as an independent variable in an econometric model. I used one of the ready-to-use models of hugging face ...
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Different scaling methods of different features results in a faux dependency between them
My dataset contains the following two features: "movie duration" (minutes) and "tv shows duration" (seasons). If a certain sample is of type "movie", it's duration will ...
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Can DeepSort be made to track objects beside people?
As far as my understanding goes, the model used for feature extraction in DeepSort is specified as the first argument of the function create_box_encoder in the file ...
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FTT Features to use after time-domain is transformed to frequency-domain
Please forgive the question if it sounds trivial/naive, I am from computer science background, not electrical/computer engineering.
I work with GPS trajectory dataset for classification. Data was ...
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Best Feature Extraction Practise for Long Audio Data
I have a video dataset and my aim is classifying predefined scenes in these videos at 1fps (that means I perform classification at each second). Therefore, I plan to fuse audio and visual features for ...
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What's the best way to handle unclassified data in a dataset when using a decision tree-based classification model in Python?
I trained a model that performs classification using decision trees.
I will use my model to perform classification on my dataset.
My dataset also contains data that does not belong to any class in the ...
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How to treat single column with both continuous and categorical data for ML model
I am working on financial data where I have a feature(column) with 90% values between 0-1000 (continuous) and 10% values as -1, -2 and -9. (default values)
Default value definition:
-1: data not ...
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What is the steps to generate data from a plot and use them to have a predication using python?
I have a plot that represent a BH curve for magnatic material. The material have a behavior for each H value for two different temperature 25 C and 100 C. Figure 1. I need to extract the data for each ...
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Making a netcdf data using xarray
I am very very new to the world of data science as I only started using it in my new job so I would really appreciate help from the community experts (maybe also in simple words :)).
I am trying to ...
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Why use feature-hashing instead of just remove random words from Bag-of-words?
As far as I understand Feature-Hashing ("Hashing Trick") is that we map some string to an index in an array e.g say we want the resulting dimension of our array to be 5, then maybe the text <...
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autoencoder feature extraction
I'm very new to deep learning and come across an idea of feature extraction by using autoencoder. I went through many example online and came across these following.
https://www.thepythoncode.com/...
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MEL VS linear spectrograms for bioacoustics machine learning
I don't have background in bioacoustics but working on a data-science project in bioacoustics.
I am working with animal vocalizations recorded at sampling rate of 250000.
Animals are bats, which are ...
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What ML techniques could be used for biometric feature extraction and ID generation?
I'm working on a project that involves generating a unique ID for a given biometric (such as an iris image). I'm interested in exploring the use of ML techniques for feature extraction and ID ...
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Can't concatinate texture_features and resnet50_features
I have extracted resnet features(array) and texture features(list) of my image dataset. My idea is to concatinating both of the features and then use the merged feature to fit the model.
Code snippet:
...
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How to extract embeddings from an audio file using wav2vec along with context
I am trying to use wav2vec embeddings from the XLSR model for emotion recognition on the EMODB dataset. How can I extract embeddings using wav2vec?
I want to use the XLSR model pre-trained with ...
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Issues with audio embedding using wav2vec
I am having issues with audio embedding using the wav2vec library while trying to classify emotions using audio signals from the EMODB dataset (Emotions dataset in German). I am using the following ...
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Boosting the effect of some of the features in SVM
I'm doing text classification with SVM. I'm using Tfidf vectorization. In addition to the text vectors, I have a context data denoting the possible outcomes of the prediction. For example, I have a ...
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Using features extracted from CNN and handcrafted features to perform classification
I have a question in regards to merging features extracted from CNN and handcrafted features.
I have been reading this paper https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9002895/#B33-sensors-22-02467
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Feature extraction using autoencoder produces latent vector with large elements
Good day.
I am experimenting with a convolution autoencoder, represented below, for feature extraction. The latent vectors have large numbers, > 10 and < -10, that cause problems for later ...
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Which Feature Selection Techniques for NLP is this represent
I have a dataset that came from NLP for technical documents
my dataset has 60,000 records
There are 30,000 features in the dataset
and the value is the number of repetitions that word/feature appeared
...
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which features are most important for skin diseases classification?
I am working on skin problem detection and am using a skin image dataset. I want to extract features from the images, but I can't understand which handcrafted features I should extract. I did some ...
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Why plot features?
In PyTorch's tutorial, Speech Recognition With Wav2Vec2, the acoustic features are extracted from the audio waveform (even though it was unnecessary, as the model can perform feature extraction and ...
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Feature Extraction using deep learning but classification Using boosting or other ML algorithms
Is it logical to perform feature extraction using deep learning but classification using traditional machine learning or boosting techniques at the same time?
Is it okay to use ML algorithms for ...
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Minimum number of items required to build a good hybrid recommender system?
I am trying to build a hybrid recommender system using lightFM that only recommends one of $3$ items. In my case, they are marketing campaigns that a company would like to recommend for users at a ...
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Feature selection and model performance
Featuretools provides an automated way to generate features from your data, by providing relationships within your data and applying their so-called deep feature synthesis. It generates features like ...
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Handling of readability scores for short texts
I have a classification problem using emails as my dataset.
I would like to use scores from various readability formulas as features for the classification. However, most of them are defined for ...
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Autoencoder vs Pre-trained network for feature extraction
I wanted to know if anyone has any sort of guidance on what is better for image classification on a lot of classes (about 400) with a small amount of samples per class (around 20), for relatively big ...
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Using the results of clustering to retrain a neural network
I am following and expanding upon previous work from the winner of the Melanoma Classification from here.
The dataset has 9 classes. The competition is only interested in the one class (Melanoma).
I ...
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Min Pooling vs Max Pooling
If I train a simple CNN with an MNIST dataset for digit classification. Is it possible to get a similar performance if I replace the max-pooling layers with the min-pooling layers?
This problem may be ...
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How to build a predictive model with multiple features?
I built an R RandomForest Regression model. The source training data is a historical monthly report of all closed tickets, and the data for forecasting/prediction is a report of open tickets. These ...
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Feature Engineering Encoding for multiple category with huge category range
I need to encode a column "Tags" that has a total of 144 different types and at the same time a row can contain multiple tags. What's the best encoding method in this situation?
One-hot ...
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Is the result of my feature encoding numeric or categorical?
I have the following categorical feature in a data table (recording the day of week when a certain action happened):
...
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How can "profiling" be done in a dataset? What are the different techniques?
I am currently doing an analysis in which I need to "profile" each record. For example, let's say I have a dataset of accounts with customer information (name, id, address, money spent, ...
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High level-Low Level features in U-NET
Why do the first layers of U-Net or CNN generate low-level features? Why not the last layers? What is the logic behind getting low-level features at the beginning of architecture? And yes, high-level ...
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How to select relevant columns from a dataset with many features
I have a dataset with a large number of potential features (>100) and I am interested in finding a relatively small subset of these (maybe on the order of 5, or 20) features which is best suited to ...
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Automated feature selection - Best practice to avoid data leakage?
This question relates generally to all automated feature selection approaches. In my particular scenario, we have a python package called tsfresh and multiclass classification.
What has been done so ...
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What can we learn from visualizing Feature Maps
I have the following classification model (dogs vs cats):
...
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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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