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.

Filter by
Sorted by
Tagged with
0
votes
0answers
26 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 ...
2
votes
1answer
21 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 ...
0
votes
0answers
17 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: ...
1
vote
1answer
21 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 ...
0
votes
0answers
19 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: ...
1
vote
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 ...
1
vote
0answers
12 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 ...
1
vote
0answers
7 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 ...
1
vote
0answers
35 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 ...
0
votes
0answers
9 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?
0
votes
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 &...
0
votes
0answers
7 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 ...
1
vote
1answer
22 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 ...
0
votes
0answers
7 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 ...
0
votes
2answers
90 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,...
0
votes
1answer
18 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 ...
0
votes
2answers
33 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 ...
3
votes
2answers
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, ...
1
vote
0answers
32 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 ...
1
vote
1answer
30 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 ...
1
vote
1answer
75 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 ...
0
votes
1answer
26 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 ...
1
vote
2answers
38 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 ...
2
votes
1answer
30 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 ...
0
votes
1answer
41 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 ...
0
votes
2answers
32 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 ...
0
votes
0answers
18 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: ...
0
votes
1answer
24 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 ...
0
votes
0answers
32 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 ...
0
votes
1answer
130 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 ...
0
votes
0answers
12 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: <...
2
votes
1answer
37 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 ...
0
votes
0answers
25 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 ...
1
vote
0answers
23 views

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 ...
1
vote
1answer
82 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 ...
0
votes
2answers
62 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 ...
0
votes
0answers
8 views

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 ...
0
votes
1answer
41 views

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. ...
0
votes
1answer
47 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?
1
vote
1answer
56 views

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 ...
0
votes
0answers
34 views

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 ...
0
votes
0answers
15 views

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 ...
0
votes
2answers
200 views

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-...
0
votes
0answers
19 views

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, ...
0
votes
0answers
8 views

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 ...
1
vote
1answer
39 views

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 ...
1
vote
2answers
103 views

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 [...
1
vote
1answer
19 views

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 ...
2
votes
1answer
47 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....
0
votes
0answers
9 views

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 ...

1
2 3 4 5
7