Questions tagged [features]

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Hard time finding literature on feature clustering using Principal Component Analysis

Im new to StackExchange, so i am sorry if this is not the right way to ask a question on StackExhange. For my thesis I wish to propose a methode for future research on using PCA to cluster features (...
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LSTM for binary classification using multiple attributes

I haven't used neural networks for many years, so excuse my ignorance. I was wondering what is the most appropriate way to train a LSTM model based on my dataset. I have 3 attributes as follows: ...
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Relation between Features & Polynomial Equations in Machine Learning

In Machine Learning, if the data we are working on has, say, 6 features/variables, does that mean the prediction line/curve of our ML model is represented by a Hexic polynomial equation whose degree ...
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Feature engineering before splitting

This is a sister post to the original closed post (here). Since the data transformation part is done after data spliting on the TRAINING data only, I wonder wouldn't such transformation has dependency ...
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Is there a multi-modal population based metaheuristic that is non-GA?

I have a feature set from which I want to select various combinations and permutations of the features. The length of a solution feature vector can range between , say 5 - 20 features , and the ...
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1 answer
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Is there a way to combine multiple ML models where each use datasets with different features?

I have a dataset where some features (c,d) apply to only when a feature (a) is a specific value. For example ...
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1 answer
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train-test split on forecasting a time series using external features

I have a question regarding the train-test split when forecasting a timeseries using features instead of the time series itself. I know that I should use a time-based train-test-split if i use lagged ...
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Finding attributes that make up dense clusters of fraudulent transactions

I have data about purchases customers made in my website. Some users later decline the purchase, a scenario I'd like to avoid. I have lots of data about the purchases made in my website, so I'd like ...
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Feature Map setup for Faster RCNN with resnet50 backbone

I'm trying to get an activation map using a Faster RCNN Resnet50 backbone, but am having issues getting the proper hook setup for output information. Most of the libraries, like gradcam, don't seem to ...
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1 vote
0 answers
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vertical or horizontal storage of timesteps in feature store

I'd like to use a feature store to store some time series and I asked myself what's the best way to store the timesteps. Is it better to store each timestep horizontal and then doing windowing after ...
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How can I assess feature importance when determining whether a missing data is MCAR or not?

I was reading some lecture notes on missing data and the author suggests the following approach to determine whether some varibale is missing completely at random (MCAR) or not: Supervised Learning ...
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1 answer
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Query regarding the 'Data type' of features in Machine Learning

Should all the features in a dataset be converted to the same data type? For instance, if all the features have numerical values, some int & some float, should they all be converted to float? What ...
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2 votes
1 answer
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Training & Test feature shape is different from number of columns in dataset

I am making a Sequential Neural Network for regression with 3 dense layers which will be trained on a simple dataset. But before I even get to that part of the code to execute the model I am getting a ...
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1 vote
0 answers
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Can regression algorithms treat multiple input features as a single feature for prediction?

I have a regression problem where I have multiple RSSI values from 3 beacons and I need to predict the x & y coordinates of the mobile object sending the signals based on the RSSI values captured ...
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1 answer
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How to choose feedforward architecture for few number of features but very large instance?

Assume I have 1 million of data instance and each instance contains 100 feature. For each instance, I also have a lable. The ...
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1 answer
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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 ...
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1 answer
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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. ...
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1 vote
1 answer
25 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 ...
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1 answer
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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 ...
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1 answer
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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 ...
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1 vote
1 answer
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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 ...
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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 ...
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2 votes
0 answers
343 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(). ...
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1 vote
2 answers
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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 ...
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2 votes
1 answer
229 views

Multi-Feature One-Hot-Encoder with varying amount of feature instances

Let's assume we have data instances like this: ...
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1 vote
2 answers
95 views

Xgboost : A variable specific Feature importance

I have a data set something like this: ...
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-2 votes
1 answer
42 views

combine two features into one [closed]

In an 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 dead ...
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1 answer
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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 ...
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3 votes
0 answers
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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 ...
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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 ...
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1 vote
1 answer
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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 ...
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1 vote
1 answer
87 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 ...
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1 vote
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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 ...
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0 votes
1 answer
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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 ...
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1 answer
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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'...
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2 answers
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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 ...
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3 votes
3 answers
346 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: ...
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1 vote
1 answer
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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 ...
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1 vote
1 answer
35 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 ...
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3 votes
2 answers
3k views

Similarity Measure between two feature vectors

I have face identification system with following details: VGG16 model for feature extraction 512 dimensional feature vector (...
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0 votes
1 answer
60 views

Classification or regression problem?

I have a table with this features: ...
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2 votes
1 answer
495 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: ...
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1 vote
1 answer
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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 ...
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3 votes
2 answers
379 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 ...
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1 vote
1 answer
42 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 ...
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1 vote
1 answer
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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 ...
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3 votes
0 answers
42 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. ...
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2 votes
1 answer
581 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 ...
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1 vote
1 answer
417 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: ...
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1 vote
0 answers
32 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 ...
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