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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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1answer
18 views

How to use efficient net as feature extractor for meta/Few shot learning in PyTorch

I am working on few shot learning and I wanted to use efficient-net as backbone feature extractor. Most of the model use Resnet as feature extractor. For example I can use below line of code and it ...
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0answers
13 views

What should be the input shape for convLSTM if ResNet-50 is applied before?

I have a video dataset, extracted all its frames, and applied ResNet-50 to extract features from all frames. ResNet-50 provides feature map of (2534, 7, 7, 2048), 2534 are the number of frames. Now I ...
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0answers
22 views

Permutation importance of features [closed]

This agnostic-model is not well addressed in research papers. I read articles where it was used to test the accuracy of the models, trying to understand the importance of individual features and their ...
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3answers
115 views

Deciding which samples the model will (probably) classify incorrectly

Problem: Given a neural network for image classification, the objective is to develop an algorithm which decides which images are 'problematic' and the model is probably going to classify them ...
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0answers
24 views

How to extract important text markers from samples to identify patterns?

Problem I have collected a decently large set of movie trailer titles from various Youtube trailer channels. I'd like to extract or infer the movie title and release year from this set in some way to ...
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2answers
26 views

Dimensionality reduction for feature extraction when missing some feature values

I have two questions: 1-Which method is appropriate for dimensionality reduction for feature extraction when missing some feature values? 2-Which textbook is the best source for the answer in (1)?
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0answers
7 views

TensorFlow - Image Vectorization - Add New Files

I am using tensorflow for feature extraction from images. Images are divided into 5 categories, each having various designs (which are labelled and trained to the system). Model is trained to find ...
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1answer
22 views

How do I get my Neural network to ignore certain values?

I was wondering if there was a way that I can get my CNN encoder-decoder neural network to completely ignore certain values in my data (2d images). There are some pixel values of 0 that never change ...
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1answer
16 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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0answers
11 views

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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0answers
58 views

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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1answer
18 views

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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1answer
35 views

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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0answers
19 views

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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0answers
26 views

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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1answer
14 views

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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1answer
15 views

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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0answers
38 views

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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0answers
10 views

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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1answer
16 views

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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0answers
85 views

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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1answer
44 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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0answers
27 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
32 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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0answers
49 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
20 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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0answers
15 views

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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0answers
8 views

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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0answers
49 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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0answers
16 views

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
151 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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0answers
15 views

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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0answers
9 views

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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0answers
9 views

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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2answers
201 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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1answer
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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2answers
40 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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2answers
44 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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0answers
41 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
33 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
311 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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1answer
186 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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2answers
54 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
42 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
52 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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2answers
42 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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0answers
28 views

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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0answers
40 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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