Questions tagged [features]
The features tag has no usage guidance.
66
questions
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0answers
26 views
How to build multiple variable regression having a mix of numerical & categorical features?
There is a need to estimate Annual Average Daily Traffic Volume (AADT).
We have bunch of data about vehicles' speeds during several years. It is noticed that AADT depends on the average number of such ...
0
votes
1answer
19 views
Non-commutative distance formula
I am trying to find a distance formula or a method that can give the non-commutative distance between two points in a feature space.
Suppose there are two movies represented in an R^n feature space. ...
1
vote
1answer
21 views
Integer encoding and weighing when one feature consists of more names [closed]
Hello I am trying to make a content based movie recommendation system and one feature is genre of the movie. I will give an integer number to each genre randomly. However, some movies are of more than ...
0
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1answer
23 views
Resampling : My dataset is categorical or numerical?
I have a dataset with 203 variables. Like age>40 (0 -yes, 1-no), gender(0 or 1), used or not 200 types of drugs (one hot encoded into 200 variables), and one target variable (0 or 1). This is an ...
0
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1answer
14 views
Using partially defined features in an unified deep learning model
Suppose we have two types of feature A and B. A is defined for all kinds of samples while B is only defined for some of the samples. Here, B is partially defined does not mean B is missing value (such ...
1
vote
1answer
13 views
Structuring extensive medical histories + demographic information for prediciting future medical outcomes
I'm looking for advice structuring extensive medical histories for predicting future outcomes, specifically hospital admissions.
Let's say I want to predict the whether or not someone will be admitted ...
1
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0answers
9 views
Latent space for cross domain numerical features
I would like to find the shared latent space between two set of features. I have source and target domain features already extracted from images. I have 4 set of feature vectors for normal and ...
2
votes
0answers
90 views
How SHAP value explains contribution of features for outliers event?
I'm trying to understand and experiment with how the SHAP value can explain behaviour for each outlier events (rows) and how it can be related to shap.force_plot(). ...
0
votes
0answers
24 views
ANOVA Feature Scoring
in order to score features, in ORANGE, using ANOVA scoring, the features should have a normal distribution?
Thank you,
J
1
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2answers
38 views
Does binning a time series with pd.qcut (using quantiles) create data leakage?
Let's say I want to predict whether a company will default on it's debt at some point in time (so binary classification) and one of the time series variables I'm using is the "revenue" of ...
2
votes
1answer
70 views
Multi-Feature One-Hot-Encoder with varying amount of feature instances
Let's assume we have data instances like this:
...
1
vote
2answers
72 views
-1
votes
1answer
18 views
combine two features into one
In a epidemic disease dataset of 3 months, I have a feature (var dt_died) with the death dates of patients (800 people died out of all 12k unique subjects in this dataset, so obviously only died ...
0
votes
1answer
41 views
Feature importance difference in two similar machine learning models
Situation 1:
I have trained a text classification model (Model 1) which gives me a probability of true class as X. I have also trained a classification model (Model 2) using only the categorical and ...
2
votes
0answers
28 views
Non-Gaussian like distributions - Classifier of source data fails on target data
I ask you for help on a classification problem (classes are represented by the numbers 0,1 and 2). All features are extracted from time series data (fundamental is sinus shape).
I have a source ...
1
vote
0answers
36 views
Self Organising Map with variable length ordered sets of N-grams
I want to preface my question with the highlighted situation I have might not be applicable to kohonen self organising maps (SOM) due to a lack of understanding on my part so I do apologise if that is ...
1
vote
1answer
13 views
distribution difference between image and text
Once for the task of image captioning I've read that, the features extracted from image and text by deep networks are from two different worlds and got different distribution. My question is how is ...
1
vote
1answer
29 views
Neural networks with not-fixed dimension for input and output
I would like to know if it exists a model/method which can deal with input and output of different dimension.
For example, let us say that the maximum number of info we could have is 6 features and 5 ...
1
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0answers
20 views
Machine learning on graphs
I'm looking for some method/model to help me with my current problem:
I have a geometry, consisting of points, and eges. For each point I take information about itself and its neighbours. For now I ...
0
votes
1answer
29 views
Terminology in machine learning: exogenous features vs external features
I am currently writing a scientific paper and do not know whether to call some of my input features of my neural network either external or exogenous.
My neural network receives as input features like ...
0
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1answer
301 views
grid search result max_features = 'sqrt' in random forest - how to understand
I did a grid search at random forest params. the result of
print(randomforestreg.best_params_)
The result is =
{'max_depth': 28, 'n_estimators': 500 ',max_features'...
0
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2answers
18 views
When combined correlation of features decreases
I'm building a machine learning model in Python to predict soccer player values. I'm trying to predict a "player_value" column containing the value of a specific player. Consider a sample of ...
0
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0answers
24 views
Feature selection by involving validation dataset
I need expert advice about a small algorithm created to perform features selection. I have used a genetic algorithm to perform features selection based on a specific objective function (good accuracy &...
3
votes
3answers
270 views
How to insert two features in a model when a feature only applies to a certain group in the model
I'm building a machine learning model in Python to predict soccer player values. Consider the following feature columns of the dataframe:
...
1
vote
1answer
33 views
Are my features enough?
I am trying to fit a regression model on a non linear data.
The features I have are around 12 and around 800 samples.
With the help of PyCaret, i tried to fit the data on to around 22 model, and then ...
1
vote
1answer
30 views
Imputing features with NA values in classification task
I currently have a dataset where each observation is a person's traffic ticket history over districts.
For each column, which represents a district:
1 represents that a person has received 1+ traffic ...
3
votes
2answers
1k views
Similarity Measure between two feature vectors
I have face identification system with following details:
VGG16 model for feature extraction
512 dimensional feature vector (...
0
votes
1answer
44 views
2
votes
1answer
150 views
How to handle a feature vector that could be variable length?
I would like to train a machine learning model with several features as input as X[] and with one output as Y. For example Every sample has a Data frame like this: ...
1
vote
1answer
45 views
File path encoding to feature
I am trying to find some sort of encoding algorithm that would allow to transform system file paths eg. "c:/users/file1/subfile2/targetfile" into a feature that I could use in machine ...
3
votes
2answers
190 views
Mathematically prove why sparsity leads to model overfitting
With respect to the stackoverflow post here: https://stackoverflow.com/a/59566478/9130959
I can't quite get why the logic stands: when # features increases, the hypothesis space is expanded, leading ...
1
vote
1answer
23 views
How Calculate Effect (percentage) label of the input variables on the output variable by DecisionTreeClassifier
a description problem below.
I have 10 words like X1 , X2 , X3 , ... , X10
and three Label like short , long , hold.
My problem is that how calculate Effect (percentage) label of the input variables ...
1
vote
1answer
15 views
What should you do with attributes that predictive in an interaction?
I am trying to predict results of football games. Some of our attributes only give meaning for a prediction only when they are considered in interaction with another attribute. To illustrate, a team ...
3
votes
0answers
39 views
NN training with repetitive features
I posted the question also on ai.stackexchange but it didn't get any answers so I though I could try here.
Here is a copy paste:
Let's say you are training a NN in a RL setting where the state (i.e. ...
1
vote
1answer
290 views
Getting the positive impacting features using SHAP
I'm attempting to use SHAP to automatically extract feature names that have a positive impact on my regression models. On inspection of the code I see that the bar plot, for example, determines these ...
1
vote
1answer
197 views
Why linear regression feature coefficients become super large?
Introduction
I've implemented linear regression using sklearn and after all calculations I've got results like this:
...
1
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0answers
25 views
Multivariate LSTM RNN DNN returning multiple features for forecasting a time series in Python
I am using the latest installation of Keras with Python 3.6 on Linux Mint with a NVIDIA (NVDA) 2070 GPU.
I am looking up. How to get the return values of my data? How do I use all of the features, and ...
-1
votes
1answer
27 views
How to select the best features for Support Vector Classification
I have a feature set that contains approximately 2 dozen features of technical analysis indicators. My own domain knowledge tells me that some of these features are better than others for predicitive ...
1
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0answers
18 views
Feature engineering one step at a time or in bunches?
Currently, I'm working on my very first classification project. If you want to know what dataset I'm working with, think "playing stairway to heaven in your local guitar store", and it will probably ...
1
vote
0answers
21 views
Which outlier detection algorithms give a breakdown of the contribution from each feature?
I am looking for an algorithm that outputs a breakdown of which features contributed the most towards a data point being labelled as an outlier.
It can be supervised or unsupervised.
At the moment, ...
1
vote
0answers
143 views
Keras most important features for text classification
I am working on a problem where I need to classify phrases in one of the two categories (let's A & B). I used the Keras SepCNN model (similar to this) for that and it is giving me some results.
...
5
votes
1answer
5k 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
154 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
43 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
2answers
71 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
177 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
26 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
154 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?
5
votes
2answers
1k 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
21 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, ...
