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
627 views

Time Series pattern recognition and classification problem

I have some labeled sensor data. Now, I would like to know how to extract features from time series using DFT, DWT, and HAAR transforms. I know that the transformations above transform a signal to ...
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0answers
196 views

What are the rules when extracting SVO triples from preprocessed text?

If you have some already preprocessed text that is tagged, what are the rules to extract SVO triplets if you want a triple like (word, word, word). Can you give the sentence as example and extract all ...
3
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1answer
142 views

Extract features from a survey

I need to use the answers from a questionnaire for training a classifier. I discovered that some questions can have nested sub-questions.. Let's say (just an example) that I want to predict whether a ...
2
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1answer
17 views

Text vectorizer that capture feature offset in the text?

I'm using sklearn Tfifdfvectorizer to extract feature from text towards text classification. I believe the information I need tends to be in the beginning of the document, so I would like to somehow ...
2
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0answers
12 views

features to help distinguish between document images

we are trying to build a model to classify different types of documents as the first step in our pipeline (final goal is to read all the text). Currently we use ImageNet to extract the features and ...
2
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1answer
86 views

What to do with large number of collinear variables?

I have this time-series dataset that has 63 features, out of which 57 were manually engineered. While checking for collinearity, I get this correlation matrix: As can be seen there are a number of ...
2
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0answers
11 views

Confusion regarding prediction results of SVM and ANN on feature vectors

I am making a custom image classifier using Transfer Learning on Inception V3. I have 3 classes of images with ~6K images each. The input dimension of the network is 500X500 and the output of the ...
2
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1answer
59 views

What are the audio features to best describe a music?

I'm working on the content-based filtering part of a recommender system for an audio streaming project. I firstly used the k-mean algorithm with music genres and one-hot encoding to classify musics ...
2
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0answers
31 views

Using datasets to predict the results for other devices

I have a datasets that contain results from a series of physical tests. It has about a dozen features and the outcome of each test is distinguished by 3 different classes. The dataset includes ...
2
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0answers
113 views

how to extract the Top contributing labels/words in universal-sentence-encoder-large - TransformerModel?

I'm using the universal-sentence-encoder-large (Transformer Model) encoding process for embedding and then using the embedding for Clustering - Basically for unsupervised learning. I want to get the ...
2
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2answers
113 views

A suitable feature vector for images

I have a set of images of various products from different websites. I want to cluster the images based on the product shown in the image. How can I generate a suitable feature vector for an image for ...
2
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0answers
109 views

Layman's explanation of when to use which smoother algorithm/technique: FFT, loess, Savitzky-Golay, etc

As an analytics practitioner, I frequently come across noisy data (e.g. IoT data). When building a model or machine learning algorithm, it can be advantageous to smooth this data. Over the years, I ...
2
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0answers
317 views

How to tune parameters for Time Series Analysis, when forecasting is only dominated by one feature and error is not getting reduced?

I am trying to predict time series based on 150 features. When I plot correlation of these features, I am getting 20 features with more or less importance but every model I use, it is completely ...
2
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0answers
265 views

Data augmentation / feature extraction on pre-trained convnets

I'm reading 'Deep Learning with Python' by François Chollet, which is an excellent book. He talks about using pre-trained convnets (in his example, VGG16) and then running smaller datasets to tweak ...
2
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0answers
334 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 ...
2
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0answers
63 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. ...
2
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0answers
170 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 ...
2
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0answers
170 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 ...
2
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0answers
446 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 ...
2
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0answers
1k 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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2answers
46 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 [...
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2answers
54 views

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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0answers
17 views

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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0answers
17 views

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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0answers
14 views

C3D features perform poorlyon HMDB51

I have extracted C3D features for the HMDB51 dataset and used a SVM on top of that to classify videos. The accuracy on test set is around 0.2. I used C3D network pre-trained on sports1M dataset, and ...
1
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1answer
38 views

How to extract features from long chemical names?

I have an interesting problem that I am uncertain about how to even get started. I am working on a binary classifier that will take a chemical name, encoded as a string, and predict whether it is a '...
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0answers
35 views

Extracting Features for Graph transformation

Suppose I have a directed graph G (V,E) whose transformation is defined by a library of patterns. Each vertex is of particular type. The library of patterns contain subgraphs (g1,g2,g3 etc)and it's ...
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0answers
37 views

Pipeline that cached the results

I use pandas to do feature extraction for machine learning. I hope to achieve the following: Consider I have five data processing steps done sequentially, and I execute it once, the results will be ...
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0answers
17 views

What is the use of having shared weights in later layers of a CNN?

In a CNN, all the neurons in a single layer use the same weights and bias. As a result, all the neurons detect the same feature. The early layers of a CNN detect simple features like edges and hence ...
1
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1answer
196 views

Bag-of-words model : Boolean vs. TF-IDF

When I design a document classifier using traditional feature engineering, I would prefer (to Boolean model) tf-idf model to represent a document into a vector because intuitively Boolean model loses ...
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0answers
17 views

Bayesian classification of “JSON” data

"Machine Learning over JSON" describes some issues surrounding the classification of JSON documents. Namely, Categorical Features Data is Hierarchical Missingness is Chunky The first two have fairly ...
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0answers
20 views

How to incorporate an attribute that only exists in some observations?

In a binary classification problem, some of my observations have an event that occurs. I can, obviously, add a 1/0 flag if the event occurs ("event_occurred" in the data below). However, my intuition ...
1
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3answers
417 views

How do I use TF*IDF scores for my machine learning model?

I have applied TF*IDF on the 'Ad-topic line' column of my dataset. For every ad-topic line, I get the same output: Firstly, I am unable to make sense of the output. The TF*IDF values are mentioned to ...
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0answers
100 views

Adding Fourier transform features to data

I'm working on some timeseries data which after visualising seems to be periodic(repeating at some interval), So I planned on finding the Fourier transform of the entire and pick the top n amplitudes ...
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1answer
356 views

MR images segmentation for feature extraction

I have datasets of brain MR images with tumours, the tumours are already selected manually by a physicist using Image J. I have read about segmentation, but I still couldn't understand how do they ...
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1answer
147 views

Mapping between original feature space and an interpretable feature space

I'm reading the following really interesting paper https://arxiv.org/pdf/1602.04938.pdf on local interpretable model explanations on page 3 however particularly section 3.3 Sampling for Local ...
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1answer
43 views

Tool for test/train automation

I need to test different datasets as well as different algorithm implementations. The current workflow looks like: Perform feature extraction from train set Train classifier on this features Feed ...
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0answers
67 views

Unsupervized NER + sequence tagging to extract attributes from product descriptions

I am trying to extract attribute values from product descriptions in an unsupervised way. For example, given the product title "Variety pack fillet mignon and porterhouse steak dog food (12 count)", ...
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0answers
18 views

Model an infrequent linear feature in TensorFlow

I am trying to predict energy usage of homes. I have a feature (home square footage) that is highly useful when available, but is often not available (in which case it is 0). I want TensorFlow to ...
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0answers
83 views

How does Stanford CRF encode NER string features?

Most features created by the NERFeatureFactory are strings e.g. from usePrev, useNext, ...
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0answers
33 views

Training Gaussian Restricted Boltzmann Machines with Noisy Rectified (nrelu or ssu) linear hidden units

I'm not sure how to implement this architecture. I'm following this thesis (pages 17-19) or this paper but I'm not sure how to train it. I want to use this to extract features from raw audio. I know I ...
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0answers
39 views

Features Extraction

I'm trying to compare two images (the first one is the ID's image and the second one is a selfie taken by phone) so I am wondering if can we extract features from the two images by using CNN and ...
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0answers
43 views

Feature Engineering for POS register events: Anomaly Detection

I am working on a dataset with only one variable: POS Journal Events.It has different values such as Items ordered, Order Placed, OrderItems,Discount applied, Promotion applied, order voided etc. I ...
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0answers
497 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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0answers
18 views

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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0answers
514 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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0answers
22 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
81 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
535 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 ...