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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11 views

Using extracted feature vector to perform zero shot detection

I've developed a deep learning model trained from scratch on fruits and vegetables. However, as the data is limited, I can only cover a few different types of fruits and vegetables with the model ...
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Doing feature extraction from name data?

I'm working with a genre prediction application right now, and I was curious about handling name data. I was planning to try to use that in the prediction(as a normal human can usually estimate ...
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19 views

Extracting features of the data using statistics? [closed]

May I know which statistical approach is best suited in data science to introduce new features or extract hidden features of a given dataset? For example I have a following dataset of rectangular ...
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struggling with sklearn Pipeline, FeatureUnion for NLP

I'm working on Kaggle dataset trying to classify in the Tweet is a disaster or not. I have "text" feature that I will transform using TF-IDF but I also want to use "keyword" ...
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Is it a good idea to combine fine tuning and feature extraction techniques?

I have a normal/tumor medical images dataset and, for the same patients, also the relative genomics, and my goal is to predict if a patient has a tumor by combining all the information. To achieve ...
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Would a neural network trained on extracted features have the same accuracy as a full network with frozen layers?

Let's say that I train two neural networks on the exact same dataset. The first network is a VGG19 model with frozen convolutional layers so only the top dense ...
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Regression with a feature which has its own depth

I'm relatively new to ML/Statistical Analysis, and I'm facing a dataset structured like this ...
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How can I transform a sequence into features

When Machine Learning libraries don't support categorical features those features can be one-hot encoded into a series of binary feature columns. I have a feature that represents a sequence or ...
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Using partially defined features in an unified deep learning model

Suppose we have two types of feature A and B. A is defined for all kinds of samples while B is only defined for some of the samples. Here, B is partially defined does not mean B is missing value (such ...
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How to decide which method to use TFIDF, or BOW

In a huge dataset for NLP it is taking very long time to classify my dataset therefore, trying each feature extraction method separetly is time consuming and not effecient. Is there a way that can ...
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Is it wrong to use residuals from one model as data in another model?

Why is it wrong to use the residuals from one model to fit another? Is it wrong? Is the difference down to how the residuals are used? For example, the residuals are useful features for extending a ...
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Feature vector representation

I have a clarification. I have to create a classification model for certain set of documents. We are supposed to flag it anamoly or not based on certain terms in the document. My question is the terms ...
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How many words should be taken as features in a ML problem?

I would like to ask you how many words should be taken as features in a ML program. For example, if I have 30000 distinct words to make a vocabulary, what would a good number be? I am currently ...
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How to merge multiple filters of a layer to a single filter in convolutional neural network?

In a convolutional neural network (CNN), the layer weights are learnt such that they extract meaningful features from the data. For each layer, can we merge multiple filters into a single filter after ...
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39 views

Cannot understand feature extraction

I'm following an AI course and we've just entered the deep learning chapter. Speaking about the difference between classic machine learning models and deep learning, it turns out one of the most ...
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24 views

Rolling window on uneven time series classification

I have a univariate time series data that I would like to take about 60 seconds of, extract features using tsfresh and classify into multiclass. So I might end up with a dataframe like: ...
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1answer
29 views

Creating features from raw accelerometer data

I have a dataset containing raw 3-axis accelerometer data collected from a users lower leg and I want to create a classification model (as simple as possible) that detects if the user is sat down or ...
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32 views

ValueError: Could not guess the value column! Please hand it to the function as an argument

I'm using the tsfresh library to extract features on my data but I keep getting an error: ...
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1answer
19 views

Matching Data Text of Two Place with Exception [closed]

I have data of two places name and it's address in a row and i have to match it. Data is text type, I have read, it have to convert to numeric type that generated by the text. I extracted the numeric ...
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I need help in PCA results using WEKA Tool [closed]

I'm working on an experiment using KDD'99 cupset I have 42 features. the paper I 'm comparing with concludes that 3 features with precision ..% ok are the best subset to identify the attack X. In my ...
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Use feature-importance to decide what features to increase to increase target

(Please suggest another title for this question if you like - I find it rather difficult to phrase) Say I have an ice-cream stand and I record 3 features of my customers ...
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47 views

Examples of “unusual”/non-trivial features that actually worked for improving model score [closed]

I have been working for a while in credit problems for classification and regression and on these problems I have had the necessity of improving already good performing models, for this when ...
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selecting only a certain number of top features using tsfresh

How can I select top n features of time series using tsfresh? Can I decide the number of top features I want to extract?
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1answer
73 views

What is meta- data and meta features?

I want to know what is metadata and what is meant by meta features? When I google Meta Features what I get is feature selection tool called "Meta-Feature". What is the function of feature ...
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What are the different ways to feature engineer webpage data for input into a webpage classification model?

Looking for resources on the different ways that one can manipulate webpage data to input as features into a neural net. I'm aware of a service called diffbot that claims to use a CV based method to &...
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How to store and query biometric data for an authentication system?

I am trying to design, and hopefully implement, an authentication system which centers around the use of biometric images. I plan to use different machine learning and deep learning techniques to help ...
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1answer
25 views

Sneakers representation learning

I am trying to make a model which would take an image of shoes as an input and output a meaningful N-dimensional embedding of the shoes, so that they could be searchable/comparable/clustered and used ...
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Create a single feature vector from the 2 edges of the vertex

Overview Consider the 4 examples of the right angled vertex shown below. In each example, the vertex is made up of 2 line segments- A and B, which are perpendicular, and the all examples are nearly ...
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140 views

Problem extracting words from dataframe

I have the following dataset which is a .json file: and I would like to get the first word for every string inside lista_asm, so I would like to get: jmp,push,...
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22 views

Is the result of feature extraction a feature representation?

If a use a feature extraction method on images, do I then get a feature representation or is there a different meaning behind feature representation? To my understanding, when I use a CNN on an image ...
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39 views

Problem with a feature (normal distribution + peak around 0)

I have a feature that shows a characteristic of the instances. That characteristic can be present or not. If present it shows an almost normal distribution of values (actually a bit skewed to the ...
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43 views

Dealing with highly variable feature set size

I'm trying to use machine learning for security event classification. My goal is to predict the outcome (true positive or false positive) of a specific event. An event has a set of variables in it, ...
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35 views

Handling highly correlated features [closed]

I have a data set of transactions and want to build a fraud detection model (classifier). Only 3 variables are given that could be used as input features. The number of transactions during past 3, 6 ...
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1answer
31 views

How to handle a valuable feature that is missing on 99\% of the samples in the data set?

Suppose we have an input feature that is highly predictive of the outcome we want to predict. However, the feature is missing on 99% of the samples in the data set. What is the best way to use this ...
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1answer
217 views

What's the difference between transfer learning and feature extraction in CNN?

So from what i understand, transfer learning is the fact of training a model on a dataset where you have a lot of data, then keeping most of trained coefficients, and only re-training the last layer ...
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100 views

Should I normalise image pixel wise for pretrained VGG16 model

My goal is to use pretrained VGG16 to compute the feature vectors excluding the top layer. I want to compute embedding(no training involved) per image one by one rather than feeding batches to the ...
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42 views

Can machine learning models treat a vector as a whole feature to learn

We know a ML model naturally takes a feature vector with real valued elements as input and learn to predict. But can it treat a fixed-size vector as a whole feature to learn? For example, when using a ...
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1answer
36 views

Feature Selection - Conditional Entropy

I've developed an algorithm to define conditional entropy for feature selection in text classification. I'm following the formula at Machine Learning from Text by Charu C. Aggarwal (5.2.2). The author ...
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1answer
49 views

How can I find if it is an overfitting problem?

I am new in Machine learning, and I want to detect emotions from the face. Preprocessing: I used equalizeHist to equalizes the histogram of grayscale images (JAFFE database with 213 images), in the ...
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37 views

Recommended Tutorial Videos or Books on Feature Engineering Using Python [duplicate]

I will appreciate it if you guys can recommend for me a good hands-on tutorial videos or books on feature engineering using Python. I do not want videos or books that teach only the theory behind ...
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What is the suggested way to create features (Mel-Spectograms) from speech signal for classification with ResNet?

At the moment I have this piece of code which cuts a Spectogram into fixed length tensors: ...
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1answer
26 views

How to utilize measurement accuracy metadata in classifier

Given that one wants to ascribe a class to groups of measurements using a classifier model, in what way can one include information about measurement accuracy? More specifically, is there a feature ...
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38 views

Can autoencoder latent variables to be used as features for classification?

I did some experiments on convolutional autoencoder by increasing the size of latent variables from 64 to 128. I used 4 covolutional layers for the encoder and 4 transposed convolutional layers as the ...
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260 views

How to extract audio features for each video frame using pyAudioAnalysis

I'm trying something like extracting audio features for each video frame. I know there are 30 video frames and 16000 audio frames per second in the video file. I'm using pyAudioAnalysis python lib to ...
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13 views

How to use an encoder to do feature extraction

I'm newbie with all of data science. I have a pre-trained U-Net network from which I get its encoder. Now I have to use a picture to get its features. With the whole U-Net I do this with fit method: <...
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1answer
39 views

Build Deep Belief Autoencoder for Dimensionality Reduction

I'm working with a large dataset (about 50K observations x 11K features) and I'd like to reduce the dimensionality. This will eventually be used for multi-class classification, so I'd like to extract ...
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30 views

How to handle multi-channel 2-D geo-spatial grid like data samples in machine learning with number of features associated with each grid?

I am looking into a problem wherein the whole geographic area is divided into number of bins/pixels so we get nxn matrix covering whole region. Now each bin/pixel has number of parameters/features ...
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Is there a common relationship between data inputs and the number of attainable features?

Is there a known relationship between the amount of information gain that comes from new data added to a dataset? for eg: If I have a plant watering system that tells me: An integer of how wet the ...
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1answer
118 views

Autoencoder feature extraction plateau

I am working with a large dataset (approximately 55K observations x 11K features) and trying to perform dimensionality reduction to about 150 features. So far, I tried PCA, LDA, and autoencoder. The ...
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100 views

How can access to modify feature_importances of Random Forest Classifier model?

My goal is to extract the feature importances from already trained random forest classifier and transfer them to another classifier. How this can be done? and How can access to modify ...

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