Questions tagged [features]
The features tag has no usage guidance.
36
questions
1
vote
1answer
30 views
How to get feature importance from a keras deep learning model?
In case of scikit-learn's models, we can get feature importance using the relevant attributes of the model.
I've been working on a RNN, using LSTMs for text embedding.
Is there any way to get ...
0
votes
1answer
11 views
order of features importance after make_column_transformer and pipeline
I have a data preparation and model fitting pipeline that takes a dataframe (X_trn) and uses the ‘make_column_transformer’ and ‘Pipeline’ functions in sklearn to prepare the data and fit XGBRegressor.
...
1
vote
2answers
22 views
If a categorical feature only occurs a few times in a data set, should I drop it?
I have a data set of mostly categorical variables. When I one-hot encoded them some of the features occur less than 3% of the time.
For instance the Tech-support feature only occurs 928 times in a ...
0
votes
0answers
26 views
Transform skewed ratio data (value range from 0 to 1) to reduce the skew
I want data clusters. Because my cluster algorithm doesn't work with skewed data I want to change that in advance. I have ratio data, i mean probabilities (values between 0 and 1). But these data are ...
0
votes
2answers
31 views
Can I use more features for my training data than my test data will supply?
I am pretty new to the data science game so pardon me, if the answer to my question should be a no-brainer.
We are looking at manufacturing / quality data where products are labeled 'okay' or 'not ...
1
vote
2answers
102 views
model with features of different sizes
I want to train a model (either classification or regression, doesn't matter) with features/inputs of different sizes, but I am not sure how to do it.
For example, for each data-point, feature 1 and ...
-1
votes
1answer
24 views
what features can I get from the sample?
I have dataset of 100 000 words labeled by surname(is last name / not last name)
Example:
kitchen | 0
kennedy | 1
etc.
I tried extract lenth of word, count of each letter and such simple features ...
0
votes
2answers
34 views
What's the meaning of precomputed features?
When i learn about deep learning, I found dataset with precomputed features form. Link (http://cs.stanford.edu/people/karpathy/deepimagesent/coco.zip). What's the different with usual dataset?
0
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0answers
95 views
How to use additional variables that are not available in test set?
I have additional variables in my dataset that are somewhat correlated to the continuous target variable, but that are completely unavailable in the test set. So, I'm wondering how the best to use ...
4
votes
2answers
80 views
SHAP value analysis gives different feature importance on train and test set
Should SHAP value analysis be done on the train or test set?
What does it mean if the feature importance based on mean |SHAP value| is different between the train and test set of my lightgbm model?
...
0
votes
1answer
19 views
How to choose the features for an algorithm from the given attached screenshot?
How to choose the features from the given attached heat map & correlation factor for the classification algorithm?
I have 6 different features i.e., ac233fc01403, ac233fc02eaa, ac233fc015f6, ...
0
votes
0answers
15 views
Feature Analysis to Maximize Classification
I keep coming across a pattern in problems I need to solve.
Perhaps one of you might have a suggestion on the best method to solve this one:
Assume 3 features, X1, X2, X3. X1, X2 are real valued ...
1
vote
2answers
42 views
Interpretation of PCA visualisation
I am trying to build a classifier to predict the ratings of a show during a specific time.
I have extracted around 109 features, some relating to the time field namely,
Day of Year
Month of year
...
1
vote
2answers
219 views
Finding Feature Importance in CNN's?
Let's say I have images of cars. For each image in the dataset, I have let's say 3 pictures of the same car but in different angles.
1) The first image is the picture of the car from the front.
2) ...
0
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0answers
23 views
uniform activation in untrained network?
I'm straggling with the implementation of a cnn.
I have large 3D images (160, 160, 160, 3) in input. They have been centered and scaled, both per sample and across dataset.
When i check the ...
0
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0answers
11 views
How to do feature engineering on this situation that the almost all label of high count part is 1
I get a feature-target analysis as follows：
...
0
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0answers
20 views
One feature - several units
I have a dataframe where one of the features is the Mileage expressed in some cases in $\frac{km}{l}$, while in others is expressed in $\frac{km}{kg}$, according to the combustion type of the car (so ...
1
vote
1answer
23 views
What is the level of measurement / name of the scale of list-features?
If you look at publications, you can have a dataset
title of publication
list of authors
number of pages
year of publication
The Level of measurement of "number of pages" is interval scale, the ...
0
votes
0answers
58 views
Replication of Andrew Ng's Sparse Autoencoder
for the past three days I have been trying to replicate the results presented in Andrew Ng's sparse autoencoding lecture (https://web.stanford.edu/class/cs294a/sparseAutoencoder.pdf) however I have ...
0
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0answers
8 views
Is it worth graphing a correlation plot between your features and your target?
Is it worth graphing the correlation between the most important features and the target variable after you have done either PCA or L1 Regularization to identify the most important features? I guess ...
0
votes
2answers
96 views
How do you apply hypothesis testing to your features?
How do you apply hypothesis testing to your features in a ML model? Let say for example that I am doing a regression task and I want to cut some features (once I have trained my model) to increase ...
2
votes
2answers
862 views
What is the difference between handcrafted and learned features
I am having difficulty understanding what the differences are between handcrafted and learned features.
Is it just the case that the handcrafted features are the input variables, and that the learned ...
0
votes
1answer
18 views
Reordering feature and its impact
How does reordering the features impact model training and its performance?
Per my understanding, it should not impact the model performance as weights get tuned according to feature value and not ...
0
votes
0answers
29 views
Feature selection in regression: are those features just correlated with outcome or are they causal?
When we get our variable importance plots in linear or logistic regression, we know that the features with more importance are correlated with our outcome. Are they necessarily causal?
0
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0answers
16 views
Text classification 'features imput'
I have a text classification task that consists of classifying text into classes (literary genres).
I have computed the average word length and sentence length. Also, some POS relative frequency so ...
0
votes
0answers
9 views
How to do feature engineering to the stripplot where the target, `tradeMoney`, has obviously lower than 5000 when 'rentType' is 'shared_rent'?
I am dealing with a house prediction problem.
When I am doing EDAs I find the such stripplot() as follows:
...
0
votes
0answers
11 views
We know the subspace generated from the data instances, but we cannot constitute the origin space
I was wondering, what if we know the subspace generated F from the data instances, but we cannot constitute the origin space E that can be in higher dimension, and can easily lead us to the true join ...
0
votes
0answers
27 views
How to choose feature which is used to fill another feature's missng values?
I am dealing with a house prediction problem. However, it has about 10% missing values in buildYear which is one of the most important features. I tried filling ...
0
votes
0answers
18 views
When to create ranges for numeric feature?
For example, in the Titanic Dataset, I'm trying to deal with the numeric datasets, FamilySize and Ticket (Ticket Price).
From the many solutions I've seen, a lot of people create ranges for ...
0
votes
1answer
59 views
Creating better features for clustering
I am trying clustering for the first time trying to separate my user into three categories (or the categories I though that they will should fall in).
First of all I have two tables that describe ...
2
votes
1answer
35 views
How to choose an optimal threshold for binary discretization
We know that we usually do discretizations to continuous features to remove extra information and unwanted regularities, which makes the model robust and well-predicted.
But I am wondering except ...
0
votes
3answers
39 views
How to deal with new features values in my classification model?
Lets say i have a categorical feature having a set of values equal to ['Single','Married','Divorced','Unknown']. Okay, so with the help of the other features, i create my model, i test it, all is fine ...
0
votes
1answer
52 views
Pretrained features return worse results for sklearn classifier/pipeline
So I have a following scenario:
Pipeline, that transform text/dict/numerical data and classifies the result with linear regresion. It looks something like this:
...
1
vote
2answers
63 views
Input data of variable length - two scenarios
I'm trying to figure out how I could train a neural network with inputs that have variable length. This issue comes up in the following 2 scenarios I'm trying to solve.
Scenario 1:
I have a long list ...
1
vote
1answer
322 views
Should unique vectors (SIFT descriptors) be used in K-Means Clustering?
I'm doing image classification by extracting SIFT features, clustering them and then finding BOVW histogram and classifying.
I have around 180 training images from which I'm extracting SIFT ...
0
votes
4answers
223 views
How can I use Machine learning for inter-relationship between Features?
Machine learning is used mostly for prediction and there are numerous algorithms and packages for this.
How can I use machine learning for studying inter-relationships between features? What are ...
