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
65
votes
11answers
34k views

What is dimensionality reduction? What is the difference between feature selection and extraction?

From wikipedia, dimensionality reduction or dimension reduction is the process of reducing the number of random variables under consideration, and can be divided into feature selection and ...
31
votes
6answers
18k views

Encoding features like month and hour as categorial or numeric?

Is it better to encode features like month and hour as factor or numeric in a machine learning model? On the one hand, I feel numeric encoding might be reasonable, because time is a forward ...
29
votes
3answers
10k views

What is a good way to transform Cyclic Ordinal attributes?

I am having 'hour' field as my attribute, but it takes a cyclic values. How could I transform the feature to preserve the information like '23' and '0' hour are close not far. One way I could think ...
29
votes
6answers
9k views

Are there any tools for feature engineering?

Specifically what I am looking for are tools with some functionality, which is specific to feature engineering. I would like to be able to easily smooth, visualize, fill gaps, etc. Something similar ...
22
votes
3answers
14k views

Why do we convert skewed data into a normal distribution

I was going through a solution of the Housing prices competition on Kaggle (Human Analog's Kernel on House Prices: Advance Regression Techniques) and came across this part: ...
22
votes
3answers
9k views

Feature Transformation on Input data

I was reading about the solution to this OTTO Kaggle challenge and the first place solution seems to use several transforms for the input data X, for example Log(X+1), sqrt( X + 3/8), etc. Is there a ...
19
votes
3answers
11k views

How to perform feature engineering on unknown features?

I am participating on a kaggle competition. The dataset has around 100 features and all are unknown (in terms of what actually they represent). Basically they are just numbers. People are performing ...
18
votes
5answers
23k 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 ...
18
votes
3answers
41k views

Feature extraction of images in Python

In my class I have to create an application using two classifiers to decide whether an object in an image is an example of phylum porifera (seasponge) or some other object. However, I am completely ...
17
votes
2answers
5k views

How to choose the features for a neural network?

I know that there is no a clear answer for this question, but let's suppose that I have a huge neural network, with a lot of data and I want to add a new feature in input. The "best" way ...
13
votes
1answer
7k views

What is difference between one hot encoding and leave one out encoding?

I am reading a presentation and it recommends not using leave one out encoding, but it is okay with one hot encoding. I thought they both were the same. Can anyone describe what the differences ...
13
votes
2answers
4k views

What features are generally used from Parse trees in classification process in NLP?

I am exploring different types of parse tree structures. The two widely known parse tree structures are a) Constituency based parse tree and b) Dependency based parse tree structures. I am able to ...
11
votes
3answers
3k views

Unsupervised feature learning for NER

I have implemented NER system with the use of CRF algorithm with my handcrafted features that gave quite good results. The thing is that I used lots of different features including POS tags and lemmas....
11
votes
3answers
4k views

How to use GAN for unsupervised feature extraction from images?

I have understood how GAN works while two networks (generative and discriminative) compete with each other. I have built a DCGAN (GAN with convolutional discriminator and de-convolutional generator) ...
10
votes
3answers
15k 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 ...
9
votes
2answers
14k views

List of feature engineering techniques

Is there any resource with a list of feature engineering techniques? A mapping of type of data, model and feature engineering technique would be a gold mine
9
votes
1answer
280 views

How does a convolutional ply differ from an ordinary convolutional network?

I am currently working on recreating the results of this paper. In the paper they describe a method for using CNN for features extraction, and have a acoustic model that is Dnn-hmm and pretrained ...
8
votes
4answers
2k views

Is (manual) feature extraction outdated?

I recently attended a PhD thesis defence in which one committee members claimed that "manual feature extraction is outdated. Nowadays, we have [deep] machine learning models doing that job for us ...
8
votes
1answer
1k views

Document classification: tf-idf prior to or after feature filtering?

I have a document classification project where I am getting site content and then assigning one of numerous labels to the website according to content. I found out that tf-idf could be very useful ...
8
votes
3answers
1k views

What is the ideal database that allows fast cosine distance?

I'm currently trying to store many feature vectors in a database so that, upon request, I can compare an incoming feature vector against many other (if not all) stored in the db. I would need to ...
8
votes
3answers
216 views

Why do RNNs usually have fewer hidden layers than CNNs?

CNNs can have hundreds of hidden layers and since they are often used with image data, having many layers captures more complexity. However, as far as I have seen, RNNs usually have few layers e.g. ...
8
votes
2answers
1k views

Averaging two Word2vec vectors to obtain a unified representation for single word

I have been working on a trained data for Word2vec algorithm. Since we need words to stay as original we don't make them lowercase at the preprocessing phase. Thus there are words with different ...
7
votes
4answers
1k views

Feature extraction from a scatter plot

Say I have a scatter plot like this: Since I have many scatter plots like this I want to do feature transformation i.e. squash (x,y) in a single term to be input ...
7
votes
3answers
362 views

Explain output of a given classifier w.r.t features

Given a binary classifier, is it always possible to explain why it has classified some input as a positive class ? And by that I mean, if we have a big set of features, is there a tool that says : '...
7
votes
1answer
2k views

Attributes extraction from unstructured product descriptions

I am trying to match new product description with the existing ones. Product description looks like this: Panasonic DMC-FX07EB digital camera silver. These are steps to be performed: Tokenize ...
7
votes
1answer
2k views

How to extract features and classify alert emails coming from monitoring tools into proper category?

My company provides managed services to a lot of its clients. Our customers typically uses following monitoring tools to monitor their servers/webapps: OpsView Nagios Pingdom Custom shell scripts ...
6
votes
7answers
4k views

How to define a distance measure between two IP addresses?

I have IP addresses as feature and I would like to know how much two IP addresses are similar to each other to use the difference in an Euclidean distance measure (in order to quantify the ...
6
votes
3answers
7k views

How to deal with categorical feature of very high cardinality?

I would like to train a binary classifier on feature vectors. One of the features is categorical feature with string, it is the zip codes of a country. Typically, there is thousands of zip codes, and ...
6
votes
1answer
177 views

Clustering strings inside strings?

I am not sure whether I formulated the question correctly. Basically, what I want to do is: Let's suppose I have a list of 1000 strings which look like this: cvzxcvzxstringcvzcxvz ...
5
votes
3answers
206 views

How does Doc2Vec treat numerical data which is a part of text data?

I have data containing both numbers and raw text related differently like: The power of diesel generator is 15kva. I need a single phase generator. Three phase generator required of 140 kva. Need 70g/...
5
votes
1answer
114 views

Why is duplicating inputs bad?

I am trying to predict an output value based on several continuously-valued inputs using a regression model. I am not sure what approach is appropriate to scale/transform the input data for the ...
5
votes
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 ...
5
votes
1answer
3k views

How to transform raw data to fixed-frequency time series?

How to transform raw data to fixed-frequency time series? For example I have the following raw data in DataFrame ...
5
votes
3answers
29k views

Extracting Features Using TensorFlow CNN

I'm trying to extract features of set of images. I'm using CNN from this site. Can anyone please tell me how to do feature extraction of images using CNN? I looked for various places. But nowhere it'...
5
votes
4answers
547 views

Couple PCA plot and clusters to labels

I am trying my first 'project' concerning machine learning and I am a bit stuck. However, I am not sure if it's even possible but here goes my question. What I want to achieve is clustering user ...
5
votes
1answer
1k 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 ...
5
votes
3answers
13k views

Using python and machine learning to extract information from an invoice? Inital dataset? [closed]

DISCLAIMER: I have absolutely no background with machine learning/data science, and am unfamiliar with the general lingo of data science, so please bear with me. I'm trying to make a machine learning ...
4
votes
2answers
3k views

What features from sound waves to use for an AI song composer?

I am planning on making an AI song composer that would take in a bunch of songs of one instrument, extract musical notes (like ABCDEFG) and certain features from the sound wave, preform machine ...
4
votes
3answers
11k 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 ...
4
votes
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 ...
4
votes
3answers
2k views

What's the best way to use binned data in a tree-based model?

I have some numeric data that has come 'binned', but the bins are not of equal sizes in terms of scale or quantile For example, an age variable that is [0-16), [16-21), [21-30), [30-45), [45-65), [65,...
4
votes
2answers
4k views

What is the rationale for discretization of continuous features and when should it be done?

Continous feature discretization usually leads to lose of information due to the binning process. However most of the Top solutions for Kaggle Titanic are based on discretization(age,fare). When ...
4
votes
3answers
2k views

Categorizing Customer Emails

I am working on a project for a company which needs to categorize customer e-mails regarding loans and insurance. The e-mails are labeled uniquely from set of 13 category labels. The number of records ...
4
votes
2answers
9k views

Pivoting a two-column feature table in Pandas

How can I transform the following DataFrame into one with cities as rows and each cuisine as a column, and 1 or 0 as values (1 if the city has that kind of cuisine)? I think this turns out to be a ...
4
votes
2answers
150 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 ...
4
votes
1answer
963 views

Can RNN be used for feature extraction?

I was reading this paper and my question is related to it. What I am stuck at is the intuition behind using two CNNs for feature extraction. Can just RNN not be used for feature extraction as well as ...
4
votes
2answers
106 views

Blind feature engineering

I received a dataset for analysis that had ~100 numeric columns with anonymous column names($X1$, $X2$, $X3$, etc...) and asked to do a binary classification. My resulting classification algorithm ...
4
votes
1answer
349 views

How and Why to rescale image range between [0,1] and [-1,1]

I am trying to implement model described in Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network in which author says in section 3.2 that We scaled the range of the ...
4
votes
1answer
283 views

What is representation in optical character recognition?

I am learning OCR and reading this book The authors define 8 processes to implement OCR that follow one by one (2 after 1, 3 after 2 etc): Optical scanning Location segmentation Pre-processing ...
4
votes
1answer
5k views

Use TSFRESH-library to forecast values

Have some issue with understanding how to use TSFERSH-library (version 0.4.0) to forecast next N-values of particular series. Below my code: ...

1
2 3 4 5 6