Questions tagged [features]

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14 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 ...
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18 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 ...
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20 views

Defining features in an LSTM [on hold]

I want to feed an LSTM model with $12$ different time series features. Now I want to know how I can implement this and what ...
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1answer
18 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 ...
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20 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 ...
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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 ...
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2answers
33 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 ...
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2answers
106 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 ...
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1answer
17 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 ...
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27 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?
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14 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 ...
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7 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: ...
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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 ...
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26 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 ...
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13 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 ...
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1answer
47 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 ...
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1answer
27 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 ...
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3answers
35 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 ...
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1answer
37 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: ...
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2answers
39 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 ...
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1answer
147 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 ...
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4answers
95 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 ...