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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10 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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Alternative to creating 70 regular expressions in Python [closed]

I have a text file with lots of messy and jumbled data in it. The simplified file looks somewhat like: ...
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28 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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What is the state of the art in deep learning for image feature representation? [closed]

I am relatively new to deep learning and want to build a model that extracts features from images which i can then use for classification or anomaly detection. I have searched for quite a while now, ...
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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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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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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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23 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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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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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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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
32 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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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
23 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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55 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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Are there labeled multivariate time series data sets where only a subset/partial number of time series is relevant for each class?

I am looking for a data set of multivariate time series data which contains classes that only require a subset of time series for their identification. Assume a human activity recognition data set ...
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Single image feature reduction at inference time : SVM

I am trying to train a SVM classifier using scikit-learn.. At training time I want to reduce the feature vector dimension. I have used PCA to reduce the dimension. ...
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1answer
21 views

How to combine the features extracted from different CNN architectures? [closed]

I want to combine the features extracted from different CNN architectures into my fully connected layer. How to proceed?
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How to access the data of the column on which some groupby operation has been carried out? [closed]

Suppose there is a pandas dataframe which has one column consisting of names of something, and there are multiple entries respective to each entry in the first column. To count the number of entries ...
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Storing Audio features to a csv file using pyAudioAnalysis

I'm trying to store MFCC feartures of an audio file to a csv file. I'm following the wiki on github for Feature Extraction using pyAudioAnalysis. The suggested command is: python3 audioAnalysis.py ...
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Should feature selection give observable patterns?

I have a dataset of 7 trips on a vehicle, where a component fault occurred on the 4th trip and was fixed following that. The goal is to predict when the fault will occur for similar datasets. The ...
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Conv1D relu: negative values or additional sequence?

If I have sequences that can have negative values with occasional spikes in both positive and negative directions I'd like to preserve, what is the best practice to handle those sequences: should I ...
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2answers
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How do stacked CNN layers work?

The internet is full of pictures like this: But how are the second/third/etc CNN layers able to extract features when the features are already extracted by the previous layers? For example, the mid-...
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Dimensionality Reduction on Cross Channel EEG data

I'm working on a project predicting seizures events using 10 minute EEG data recordings. This involves identifying the preictal (pre-seizure) phase from the interictal (normal/between seizure) phase, ...
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Factor Analysis with Mixed Data gives many components

I performed Factor Analysis with Mixed Data using PCAmixdata package from R. My dataset consists of 115000 records with 40 features of both categorical and continuous data. I checked the eigenvalues ...
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File path encoding to feature

I am trying to find some sort of encoding algorithm that would allow to transform system file paths eg. "c:/users/file1/subfile2/targetfile" into a feature that I could use in machine ...
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What are some good methods to forecast future revenue on categorical and value based data?

I have monthly snapshots (3 years) of all the contract data. It includes following information: Contract status [Categorical]: Proposed, tracked, submitted, won, lost, etc Contract stages [...
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1answer
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Is there any problem with dropping only part of the OneHot generated features?

The one hot encoder adds more columns to the data, one for each category in the encoded feature. In the example below, the column City was transformed into 4 other ...
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1answer
41 views

Finding a range of values for each feature that contribute to positive classification

Consider a classification problem(lets say 2 classes, 'good' and 'bad), where all features are continuous. what I need is a range of values for each feature that contributes to 'good' classification....
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Extracting the features from several Auto Encoders

I am trying to extract the features of sparsed 3D pictures via a Convolutional Auto Encoder(CAE). Dou to the high computational costs I can not train the CAE over all the samples. I prepared couple of ...
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Importance of features

It is common to say in ML feature selection that features that are irrelevant in isolation can be important in combination with other features. Is there a simple example (one or two features) to ...
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9 views

Creating a new unique feature from existing features and using it instead in neural networks

Lets say I have 3 features a,b,c and lets say I am sure they vary between 0 to 100. Instead of feeding my neural network 3 features what happens if I create a unique number from this 3 numbers ...
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Extract information using NLP and store it in csv file

I have a text file that stores the pickup, drops, and time. SMS text is a dummy file that is used to train a cab service model. The text is like in this format: ...
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Do we train a feature extractor or we just use a trained network as a feature extractor?

I've just started to learn Tensorflow and Keras. I'm using Tensorflow 2.1.0 and Keras 2.3.7. I'm using this network as a feature extractor. Well, I'm trying to use it: ...
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Ensemble Model to Handle Different Image Attributes

I'm working on a project where I have images annotated across several attributes, say X, Y, Z...
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17 views

Categorical Feature with Most of the Data in a Single Category

I am a beginner with machine learning and I ran into something that made me question qualities for a good categorical feature in a regression model. Picture of Feature and Distribution Here. From the ...
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2answers
153 views

Mean estimation for nested location data

I want to estimate the average income for a location. I have nested data in the following way: A block is inside a neighborhood, which is inside a zipcode, which is inside a district, which is inside ...
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1answer
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How to group categorical columns into similar types?

(Forgive me if the question is ill put. I am a novice in data science. Please comment or edit so that the question can be improved) I have a dataset where we have to predict the future sale of a shop....
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25 views

Feature Selection with non-linear numerical and categorical variables

I have a dataset of 45 non-linear numerical values and 2 categorical values. I am making a feature selection to predict categorical variables one by one or together. I used the correlation ratio and ...
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1answer
19 views

Context capturing in a Structured PDF?

I'm trying to extract resume (PDF) data. resumes always tend to follow a structure. so if you see some numbers in a cv; according to the context, we could tell whether its a telephone number, a ...
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1answer
23 views

Should we do Feature selection in parallel with feature engineering?

I'm working with LightGBM on a large data set about 3M row and about 8 columns. When i ...
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70 views

Understanding sklearn FeatureHasher

Wanting to understand "the hashing trick" I've written the following test code: ...
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1answer
52 views

List of keywords as features

I'm new to machine learning, being this the first time I'm involved in a project in the area. I have a dataset of news articles and have extracted the keywords present on the news title such as ...
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Assigning points to fitted planes

I’m working on a project involving fitting planes to 3D point clouds. The actual plane fitting part is working fine, but I’m trying to decide the best way to actually bound the fitted planes by the ...
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Feature engineering one step at a time or in bunches?

Currently, I'm working on my very first classification project. If you want to know what dataset I'm working with, think "playing stairway to heaven in your local guitar store", and it will probably ...
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Upsell project based on sales records

in my company we are working on a upset project in which we are trying to solve the following problem: What we propose to our customer that he/she may be interested in based on the fact that he/she ...

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