Questions tagged [features]
The features tag has no usage guidance.
88
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Should highly correlated features be removed, even if they have different type of information?
A quick example for this: we have many feature and two of them are policy count and premium_total (for all policies). We are predicting the expected claim amount with GBM or RF. Both policy_count and ...
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51
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Shapley Values - How to interpret each value for each feature for a specific instance?
I am using Shap Values(the 'shap' module in python) to help me understand a bit better the relation between my features and my target. I am currently working on a binary classification problem.
I know ...
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How the low level features are combined to form high level features in CNN? What happens to combine low level feature to form higher ones in bw layers
I want to understand basics behind cnn features formation like how high level features are formed using low level features in a CNN?
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44
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SHAP: How can interpret a certain feature has positive or negative impact correctly?
I want to raise a question here already I created an issue in the related workaround but still haven't gotten any clarification about it.
I also want to tag most related posts I found: post1 & ...
- 385
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15
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Machine learning features - detect mean shift using expected values
I have an LGBM model that trains on machine learning features and predicts some numerical outcome with new data coming periodically. I would like to make sure that the new input data is "similar&...
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14
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How do I match the number of the features of new text data to the data used in the training of the model
I am working on a classifier for some twitter data to predict who it was tweeted by. I am only using the text of the tweets to build the model. After all text related preprocessing here is how I ...
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10
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Zernike moment calculations
I am trying to work with Zernike moments and am after all my efforts not able to understand a few things. Following is the formula I found in literature:
I cannot understand what the impact of p (...
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318
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How to select relevant columns from a dataset with many features
I have a dataset with a large number of potential features (>100) and I am interested in finding a relatively small subset of these (maybe on the order of 5, or 20) features which is best suited to ...
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How to use a material number as a feature for Machine Learning?
I have a problem. I want to use a classification algorithm. I also have materialNumber as a column. Could I use that as a feature for my Machine Learning algorithm? ...
- 89
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61
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Create features for each row or only for a specific value
I have a problem. I want to predict when the customer will place another order in how many days if an order comes in.
I have already created my target variable ...
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Reverse engineer PII sensitive data from Inceptionv3 pre-trained model generated features
I'm using the pre-trained Inceptionv3 to build out features from proprietary documents. Some of these documents contain sensitive PII data. I use the 2K output from the second last layer as the ...
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44
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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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81
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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:
...
- 101
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22
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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 ...
- 397
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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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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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116
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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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14
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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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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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295
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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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14
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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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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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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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123
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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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28
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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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360
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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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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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15
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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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17
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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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575
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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(). ...
- 385
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2
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125
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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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753
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Multi-Feature One-Hot-Encoder with varying amount of feature instances
Let's assume we have data instances like this:
...
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67
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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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410
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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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58
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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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37
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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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192
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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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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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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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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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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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27
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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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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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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
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39
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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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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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