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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433 views

DBSMOTE on Short Text Classification

I am trying to use DBSMOTE(Density-Based Synthetic Oversampling TEqnique) to on a data set of short text--tweets to be specific. This will be used to train a classifier model in a multiclass ...
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1answer
217 views

Fitting and transforming text data in training, testing, and validation sets

I'm trying to implement a simple text classifier wherein the data is split into training (70%) and testing (30%) sets, but cross validation (k=10) to be performed on the training set. My main concern ...
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1answer
57 views

How to represent relation between users as a feature?

I'm developing a model for unsupervised anomaly detection. I have a dataset representing communications between users (each example represents a communication): there are many features (time, duration,...
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1answer
126 views

BOVW - Combine vocabularies

What I have so far I have a set of images that I am trying to classify. I can also extract different feature descriptors from the images using algorithms such as hu moments, color histogram, and SIFT....
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1answer
92 views

Does it make sense to “reorder” a categorical feature to make it monotonic?

Sorry for the vagueness of the title; I'll explain what I mean. I'm doing the Kaggle Titanic beginner tutorial. The label you're interested in is the "survived" rate (0 or 1), which you want to ...
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505 views

How to extract relative importance of features from a tensorflow DNNRegressor model?

I followed these two posts to understand about restoring a saved model and then extracting variables from it: Extracting weights values from a tensorflow model checkpoint How to examine the feature ...
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2answers
207 views

Feature Engineering of mixed data type column

I have a data set in which I have to predict the price of a building. Among many features there is a feature called Availability which has two type values like : ...
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Converting MFCC to FFT

I have 128 bin FFT data for an audio file. I want to convert these FFT into MFCC of size 14, 20, 40. Is there some library which converts directly FFT to MFCC. P.S - I dont have the actual audio file....
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626 views

How to concatenate feature vectors of different dimensions?

I have been using different deep learning models and extracting features from different layers for the given images. My code goes like this: ...
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0answers
92 views

Incorporating new features in document similarity task

I have a model pipeline for finding similar text documents given an input query text. The model is very simple; I have a corpus of documents on which I train a TfIDF model. When a query is input, we ...
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4answers
787 views

Feature extraction from pure text

I have a dataset (~52k rows) with a column containing just pure sentences (upper and lowercase, with punctuation and stop words) in each row. What can I do to represent this data in a meaningful way ...
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1answer
296 views

Suitable Autoencoder for Activity Recognition dataset Feature Extraction

I have text data representing sensor outputs. Dataset: ...
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1answer
238 views

Proper/Possible methods for extracting unstructured data from websites

I'm working in Python, using Scrapy, and NLTK to try to understand how I can extract data from college websites. My scraper can navigate through the university websites and find their tuition fees ...
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1answer
221 views

What is the risk of removing a feature with low correlation…?

I'm running a linear regression model as baseline for a specific estimation problem. Based on the resulting R-squared, regressor coefficients and their respective p-values, I can conclude that ...
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5answers
28k views

Feature selection vs Feature extraction. Which to use when?

Feature extraction and feature selection essentially reduce the dimensionality of the data, but feature extraction also makes the data more separable, if I am right. Which technique would be ...
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1answer
78 views

How to manipulate this column of less than/greater than?

I have a dataset in which one column is as given in the picture. What will be the best way to handle such a column?
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0answers
23 views

How is Kernel Matrix on a distribution defined?

Consider the following words taken from the lecture notes: The Hilbert-Schmidt Independence Criterion (HSIC) measures the dependence of the two random variables $X$ and $Y$. An empirical estimate of ...
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0answers
84 views

What are best practices for collaborative feature engineering?

I work in a large company on several data science projects. For each of the projects me and my colleagues construct features that have some predictive value for the specific target in that project. ...
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1answer
1k views

Under what conditions should an autoencoder be chosen over kernel PCA?

I've recently been looking at autoencoders and kernel PCA for unsupervised feature extraction. Lets consider just for a moment linear PCA. Its my understanding that if a autoencoder (with a single ...
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1answer
53 views

Features for blink detection in real-time single channel EEG [closed]

I am looking to detect blink events in real-time single channel EEG. Classification of a moving window of samples to determine whether a blink artifact exists requires feature extraction (except when ...
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1answer
426 views

Clustering combining numeric features and weekday & hour cyclic features

The question is strictly related to What is a good way to transform Cyclic Ordinal attributes? and Ways to deal with longitude/latitude feature They presented a very clear answer about the approach ...
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2answers
390 views

How to find categorical features from a vector representation of text?

The context of the question: I have a pandas dataframe where one column has text values and others have categorical values. I trained a word2vec model with ...
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3answers
13k views

How to get spike values from a value sequence?

I have pile of vectors where the values could be plotted like this: Now I want to extract the "spike values" (over a certain threshold say 15,000). In this case there is fifteen. How could this be ...
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1answer
2k views

Extract feature vector of a CNN

How can I get the feature vector of my dataset. I have a fine-tuned CNN model with my data. Now I want to feed the features of all my dataset extracted from the last layer of the CNN into a LSTM. So ...
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1answer
318 views

Convolutional Neural networks

Hi all: I have a very fundamental question on how CNN works. I understand fully the training process as to take a bunch of images, start with random filters, convolve, activate, calculate loss, back ...
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2answers
8k views

Sklearn tfidf vectorize returns different shape after fit_transform()

I'm new to ML and trying out basic samples using sklearn. I have achieved converting text (single dimension) to numbers using TF-IDF and got the predictions correct. Now I have a different use-case ...
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0answers
91 views

statistical significance test between binary label features

I have 667 features and I want to find features that have a significant boundary between a binary class label before I apply a classification model (e.g Naive Bayes/ SVM) to improve classification ...
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0answers
176 views

Feature engineering for hierarchical data

I am working on the KDD dataset given in this link. The dataset is related to a typical recommendation systems dataset. So you find an item and information about the item. One of the information ...
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1answer
2k views

Feature agglomeration: Is it testing interactions?

I have been looking at feature agglomeration in Python's scikit-learn. According to the user guide, feature agglomeration "applies Hierarchical clustering to group together features that behave ...
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0answers
175 views

Giving Emails as Input to Machine Learning Algorithms

I want to classify emails as Spam and Non-Spam. I have a labelled dataset of 20,000 emails in TXT format. The emails are in individual files and also in one combined file. An example email looks ...
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2answers
3k views

What are the best ways to use a time series data for binary classification

I have large number of csv files and each of them are timeseries based csv files sampled at Avery 5 seconds for 2-3 mins. I have 20k such files with 200-300 variables in each file. I am aggregating ...
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1answer
208 views

Classifying time series data that overlap

I am working with Time-Series Data that has to be classified into two classes (Blue and Red) or at least Classify the data as one class (Red), I'm unable to come up with features that distinctly ...
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1answer
3k views

Comparing 2 data frames, if value is present replace with 1 or else 0

nrow(df1$v1) = 63849 nrow(df2$v2) = 3244 ifelse(df1$v2 == df$v1, 1, 0) I know this is an easy question but I tried different procedures but none of them are ...
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1answer
55 views

Why is there a difference in performance across the feature descriptors for the same imaging modality?

I've been using GIST, HOG and SURF descriptors for extracting features from different collections of Chest-X-rays and measuring performance using accuracy and area under the curve. These collections ...
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0answers
480 views

Can AlexNet outperform ResNet as a feature extractor?

I've been using the pre-trained Deep Learning models as feature extractors on a project involving chest x-ray images to detect TB. I extract the features from the layer just before the Softmax. I ...
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0answers
978 views

Preparing, Scaling and Selecting from a combination of numerical and categorical features [closed]

I'm currently working on the Titanic dataset from Kaggle. The features consist of both numerical and categorical variables and I've also engineered a few categorical variables using original features. ...
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1answer
208 views

The automatic construction of new features from raw data

Some observations are far too voluminous in their raw state to be modeled by predictive modeling algorithms directly. Common examples include image, audio, and textual data, but could just as easily ...
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1answer
295 views

Classification: How to manage data sets where one data row depends on another data row

I am trying to classify heading, image and image caption of a webpage. I am preparing data ...
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1answer
1k views

How do I represent SURF Features into Bag of Words to determine Nearest Neighbors?

I'm trying to use Speeded Up Robust Features (SURF) to get the $k$ most similar images from a set of images in my directory. I'm planning to use $k$-Nearest Neighbours ($k$-NN) for this. As far as I ...
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3answers
18k views

Can GPS coordinates (latitude and longitude) be used as features in a linear model?

I have data sets that contain, among many features, GPS coordinates (latitude and longitude). I'd like to use these data sets to explore problems such as: (1) computing ETA to drive between start and ...
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1answer
68 views

Does feature selection removes highly corelated variables?

I know that feature selection helps in removal of irrelevant features. Do they also remove redundant features(features which convey the same info as as some other feature)? If not, which methods are ...
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2answers
1k views

Variable Importance Random Forest on R

I am currently using a random forest model for classification, however I am unsure how the feature selection technique "varImp" works on R. I understand the context of variable importance, however ...
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1answer
285 views

Feature extraction from the text

I am a newbie in machine learning but I have a coursework to create program that can extract some concrete features from the given text. For example: If I want to extract number of red apples and ...
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2answers
2k views

How to rank a feature importance?

If I trained a network using Neural Network classifier, how can I know which feature was most important for predicting the target variable? I mean how to create a "feature ranking" among the features (...
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0answers
2k views

Feature extraction using autoencoder and assigning sub-features to the classes

I have a dataset with N records and D numerical attributes belonign to C different classes. ...
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1answer
131 views

stable set PCA while adding features

Is it possible to have a PCA setup (or any other dimensionality reduction technique) in a way that adding new features wouldn't require retrain downstream models that were trained on that particular ...
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1answer
1k views

Identifying important interactions between features using machine learning

Let's say I have a set of features: a, b, c, d, e, f. I'm now interested in identifying possible interactions between these features that best predict an outcome. For example, it could be that the ...
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1answer
63 views

Distance measure calculation addresses for record linking

At the moment we use different methods for record linking locations in different datasets. Theoretically given two locations we can give a prediction on how well they match (are the same). This is ...
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0answers
564 views

How to do Feature Extraction using Apache Spark

I am a newbie to Machine Learning and I have to do feature extraction for a banking application to detect / predict fraudulent transactions. I have come across few articles on Feature Extraction ...
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0answers
130 views

TSA library on R, periodogram method

Which method is implemented when using the periodogram method from the 'TSA' package on R? Is it Welch or Bartlett?

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