Questions tagged [feature-selection]
Methods and principles of selecting a subset of attributes for use in further modelling
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1answer
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Does adding new features that contain information derivable from current features help performance?
So say you have some data that consists of some values:
1.3, 0.9, 1.1
You introduce a new feature which is the average of these values: 3.3
In this example lets say that you know the average of ...
0
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1answer
12 views
Feature selection/reduction techinique for combination of features in image processing
I have a combination of features extracted from 3 descriptors, namely GLCM based feaures(correlation, homogeneity,energy and contrast ), Local binary patterns (256) and discrete wavelet transform ...
0
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1answer
6 views
Features selection in KNN
I have a naive question about using the K Nearest Neighbor algorithm: is feature selection more important in KNN than in other algorithms?
If a particular feature is not predictive in a neural ...
0
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1answer
27 views
How to handle noisy data?
I have X values such as
[0.2, 0.1, 0.3, 0.5, 20, -0.2, -0.1, -0.6, -0.8, -30]
Now I know that if the abs value is below a certain threshold, let's say 2, the y-...
0
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1answer
32 views
LightGBM - Why Exclusive Feature Bundling (EFB)?
I'm currently studying GBDT and started reading LightGBM's research paper: https://papers.nips.cc/paper/6907-lightgbm-a-highly-efficient-gradient-boosting-decision-tree.pdf
In section 4. they explain ...
1
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1answer
30 views
How can I improve a machine learning model?
I am a Machine learning newbie and i am trying my hands with a dataset which has 9 features and my aim is to figure out the optimal multi class classification model which fits my dataset.
I applied ...
0
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1answer
59 views
Concept of Cross-Entropy [closed]
Can anyone say the cross entropy Conceptually in machine learning for selecting best features, in simple way?
I confused about that.
You do not really understand something unless you can explain it ...
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0answers
10 views
categorical features encoding strategy
I have a dataset with all features in categorical(text or numeric). What is the most efficient way to encode categorical data to numeric such that information is not lost.
I want to perform feature ...
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0answers
12 views
Same feature with different representation
lets suppose that I have two different datasets (A and B), and I want to train a single machine learning model using common features between them.
One of these features called "score". Let's say that ...
0
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0answers
14 views
How to feed my categorical data into my model?
This may be a basic question, I have a categorical data and I want to feed this into my machine learning model. my ML model accepts only numerical data. What is the correct way to convert this ...
0
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1answer
21 views
Feature Selection Phase
I am trying to predict the overall age of an opportunity (creation date - closing date) this is my response variable
lets say an opportunity passes through 3 stages
to close
For example: Opp x ...
2
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1answer
74 views
Concept of Mutual Information
I want to get mutual information in iris dataset to select best feature but i confused about mutual information.
What is concept of mutual information for selecting feature?
Can anyone explain it in ...
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0answers
25 views
Combine multiple features for text classification
Recently I started reading more about NLP and following tutorials in Python in order to learn more about the subject. I'm trying to make my own classification algorithm (the text sends a positive/...
3
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1answer
46 views
Why would a fake feature with random numbers get selected in feature importance?
I'm using a sklearn.ensemble.RandomForestClassifier(n_estimators=100) to work on this challenge:
https://kaggle.com/c/two-sigma-financial-news
I've plotted my ...
0
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0answers
11 views
ExtratreesClassifier feature importance is all zeroes
I am running ExtraTreesClassifier for feature selection. My X is an array of shape(91968,10) and Y is (91968, ) of float. My code is as follows ( Sample code)
...
0
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2answers
22 views
Rule of thumb for good number of features when dealing with grouped data
I have a classification problem on clinical data where I have multiple samples for each patient. So the samples related to the same patient are somehow dependent from each other.
I know that is not ...
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0answers
9 views
How do I store/model data needed for my recommendation module?
I'm reading data from a store's product catalog, a 100mb xml file which contains product-wise attributes like prices, categories, etc.
Given a product_id, my job ...
1
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1answer
17 views
Effect of adding extra unrelated features to linear perceptron
Suppose that we are training a linear regressor (perceptron). Adding extra features that are not related to the target (e.g. randomly generated values) before training will typically ____ our training ...
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0answers
74 views
Using greedy feature selection for linear regression in Python
This is a homework problem for a machine learning course I'm taking. I'll be as descriptive as I can regarding the approaches I took, what worked, and what didn't.
We are given four types of data ...
0
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2answers
56 views
Classification for High dimensional data
I am trying to build a classification model with 1000+ features and
I am performing the below steps but I am not sure if it's the correct way to do it
Step 1. Finding Variable Importance using the ...
0
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2answers
25 views
Extracting Useful features from large convolutional layers
I have been training a convolutional neural network on emotion detection. Now, I would like to extract features for my data to train an LSTM layer. In my case, the top convolutional layers in the ...
2
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1answer
23 views
“help” decision tree by tying 2 features together
Assuming I have in my dataset 2 (or more) features that are for sure linked (for example: feature B indicates the amount of relevance of feature A), is there a way I could design a decision tree that ...
1
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1answer
24 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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0answers
12 views
how to set the positive and the negative class for sequential features selection?
I'm working and classification problem, so after choosing Random Forest as a model, I should the best features for it, for that I used "Sequential Feature Selector" from ...
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0answers
14 views
Feature Selection: Having a large number of features select those features that classify the target class best
I have time series data and I'm using the cesium package to extract several features.
Now the thing is, the number of extracted features is pretty significant. I have tried various visualizations to ...
0
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0answers
37 views
Setting attribute weights in Weka
I'm working on feature weighting techniques (chi-square, relief..) for classification tasks using Weka. Can I add these weights to the dataset's attributes? If yes, how? Do the classification ...
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0answers
16 views
How to choose Elastic-Net parameters for feature selection?
I recently came across using elastic nets for feature selection which brings in regularization to temper the sparsity properties of L1 regressions.
I would like to learn how to use elastic nets for ...
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3answers
83 views
How to find the most important attribute for each class
I have a dataset with 28 attributes and 7 class values. I want to know if its possible to find out the most important attribute(s) for deciding the class value, for each class.
For example an answer ...
0
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1answer
28 views
Which order is correct Feature Selection then Outlier Detection or vice versa?
which of these orders is correct?
First (Feature Selection) Second (Outlier Detection)
or
First (Outlier Detection) Second (Feature Selection)
0
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0answers
16 views
Looking for freely available labelled time series data sets for automated feature extraction and selection
I am looking for recommendations of big, labelled time series datasets that are freely available on the net.
My aim is to apply and evaluate methods of automatic feature generation and selection, ...
0
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1answer
47 views
how to build a predictive model without training data neither historical data
I m trying to score "how much a product is expected in the market". I created some features:
How much this product is used each year.
Where was it used .
how many product for each country.
the main ...
2
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1answer
22 views
Classifying objects based of a varying number of the same type of feature vector for each object
For a congressional session, I have created a doc2vec model of speeches made. Using the vectors from this model, I have a dataset of each congressperson, their political affiliation, and a list of the ...
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0answers
32 views
Perform Pearson's correlation and chi-squared test for feature selection in a dataset with a mixed type of features
I've a dataset of about 200 features and 5000 instances. These features comprise of different data types like percent (string like 4.50%), dollar amount (value between $0 - $1,000,000), discrete ...
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0answers
24 views
Reduce number of vectors in dataset to achieve the “same average dimensions result”?
I have many tests (rows), each with a large set of 3D vectors (features/cols). Each vector complies: Xn + Yn + Zn = 1
Simply averaging all components ...
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0answers
16 views
Does it exist feature selection/reduction techniques in $O(n \cdot d)$?
I'm curious to know if feature selection and/or feature reduction techniques exist, which are linear on number of data $n$ and on number of dimensions $d$.
References and source code are very welcome....
2
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0answers
44 views
Feature Importance Python
My dataset has around 1000 features and 30k rows.
All the feautres have value either 1 or 0. My target variable is Size which 3 classes : Small, Medium and Large. I have around 5k "small" data ...
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0answers
15 views
Suggestions on using model in production 1 test at a time
I have created an Artificial Neural Network with 4 categorical features and a binary outcome either 1 for suspicious or 0 for non-suspicious:
...
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0answers
15 views
Quantifying feature importances using Auto-encoders
I have a set of features(mixture of numerical and categorical), each of size n. I am embedding them into a dense lower dimensionality space using an auto-encoder. I want to know if it is possible to ...
2
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1answer
24 views
Select more or less features if results are almost the same
I am having a dataset of 3500 observations with 70 features each with binary labels/targets for classifications purposes.
My aim is to score more than 90% precision and the highest recall possible ...
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0answers
16 views
Serial Clustering of features
Let's say we have two categorical features A, B for N samples. Is it okay if we do say ...
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2answers
35 views
Help with creating dimensions/features
It is quite hard to name the title properly as I just started to learn ML, will try to explain here. I want to practice ML by creating Movie suggestion algorithm. I came up with the following list of ...
2
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3answers
33 views
In machine learning how to find feature interdepencies? [closed]
Given a data set of N features, wherein some the features in this set were derived from other features from the same set, I am trying to discover inter dependencies between features (something like ...
1
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1answer
35 views
Feature importance ratio
I trained a Random Forest classifier (sklearn) and consequently computed the feature importance and consequently ranked them. The forest has 100 estimators. My top 5 features with their importances ...
2
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2answers
40 views
In natural language processing, why each feature requires an extra dimension?
I am reading Machine Learning by Example. I am trying to understand natural language processing. The book used Scikit-learn's fetch_20newsgroups data as an example.
The book mentioned that the text ...
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0answers
57 views
Best way to determine the number of features for RFE
I am applying the feature selection method, RFE (recursive feature elimination), from scikit-learn to a dataset. I do not have any pre-determined number of features for RFE and would rather get the ...
2
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0answers
30 views
Metrics to evaluate features' importance in classification problem (with random forest)
I want to evaluate the importance of each of the features of a 2000x60 dataset in a classification problem with random forest.
The most widely used ones apparrently are:
Cross Entropy-Information ...
1
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1answer
11 views
Metrics/Methods for deciding duration of video retention for on-demand websites
This might be a general question but I thought this might be the best place to brainstorm. If I had a video website that only wants to retain videos on-demand for a certain number of days before ...
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0answers
29 views
Detect multicollinearity in real-life, non-normally distributed data
I am currently trying to figure out whether my data (consisting of thousands of rows, some is numerical, and some are categorical, and some are ordinal) has multicollinearities or not.
One thing I ...
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0answers
10 views
Assigning scalar values for PID for order in Neural Network
I have built a neural network using Windows Process's I started off with only two features, the file path with parent process, and the file path with child process. I am slowly adding features for ...
2
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0answers
89 views
Representing a community as a vector
My setup is this:
Suppose I have transactional data over a large period of time. The parties of each transaction are labled, and I use Louvain algorithm for detecting communities (and sub-communities)...
