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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29
votes
3answers
11k 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 ...
66
votes
11answers
35k 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 ...
36
votes
6answers
21k 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 ...
18
votes
3answers
42k 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 ...
18
votes
5answers
25k 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 ...
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 ...
11
votes
3answers
16k 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 ...
1
vote
2answers
2k 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 ...
30
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 ...
24
votes
3answers
15k 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: ...
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 ...
14
votes
1answer
8k 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 ...
12
votes
2answers
15k 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
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 ...
4
votes
2answers
96 views

Feature selection is not that useful?

I've been doing a few DataScience competitions now, and i'm noticing something quite odd and frustrating to me. Why is it frustrating? Because , in theory, when you read about datascience it's all ...
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 ...
2
votes
1answer
132 views

Different runs of feature selection algorithm giving different set of selected feature. How to choose the best set among them?

I am using the forward feature selection algorithm from MATLAB. The code is as follows: ...