Questions tagged [feature-selection]

Methods and principles of selecting a subset of attributes for use in further modelling

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Feature Selection and Outlier Detection

How does feature selection impact outlier detection and also, removing outliers impact feature selection? It could be a basic question. However, just to know the boundaries, I asked. Thanks in advance....
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Is there a certain threshold over which to accept or reject predictors based on correlation values with the target variable?

I have been working on the Titanic dataset. After some feature manipulation, I printed out the correlation values between my target variable Survived and all the ...
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962 views

Light GBM Regressor, L1 & L2 Regularization and Feature Importances

I want to know how L1 & L2 regularization works in Light GBM and how to interpret the feature importances. Scenario is: I used LGBM Regressor with RandomizedSearchCV (cv=3, iterations=50) on a ...
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ML Approach for Getting List of Observations with Similar Features (Discrete+Continuous)

I have a dataset with 19k observations. Each has approximately 448 features: - Text description turned into vectors of size 300 - 16 categorical variables represented numerically - The remainder ...
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Feature-Target correlation graphs [closed]

I have a set of features and labels with the following dimensions: where axis=0 corresponds to the number of pixels and axis=1 corresponds to the features and time, for example, 17=117 where 17 is the ...
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1answer
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Find non overlapping area between two kde plots in python

I was attempting to determine whether a feature is important or not base on its kde distribution for target variable. I am aware how to plot the kde plot and guess after looking at the plots, but is ...
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Including identifier in machine learning model as feature vs separate model for every identifier

I am new to machine learning and i am building a model to predict number of customers for the model branch at specific hour/season/other feature. I know it will be bad idea to pit id(...
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1answer
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How to match features in new records for NLP BOW

I have a dataset that has 100,000 records data in this dataset are 2 columns 1- Text 2- Class When I apply BOW of my model I get big list of features That is fine, I managed to work with them my ...
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466 views

Random Forests Feature Selection on Time Series Data

I have a dataset with N features, each one with 500 instances in time. For example, let's say that I have the following: Features ...
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Model for Differing Number of Rows per Observation

Looking to build a response model (click or no click) on marketing data which displays varying number of offers to a person. I don't want to model which offer they click but do they click any of the ...
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1answer
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ValueError trying to use a pickled scikit-learn model

I am new to data science and trying to learn something. I was able to complete the prediction with 98% accuracy and i saved it as pickle model. Now while trying to predict using this model I am ...
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Regression performance with Feature Selection

I would like to ask you a theoretical question. In my project I am trying to get a better performance from my regression model by feature selection methods, especially with CatBoost feature ...
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3answers
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How to combine categorical and continuous input features for neural network training

Suppose we have two kinds of input features, categorical and continuous. The categorical data may be represented as one-hot code A, while the continuous data is just a vector B in N-dimension space. ...
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2answers
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How to choose the features for a neural network?

I know that there is no a clear answer for this question, but let's suppose that I have a huge neural network, with a lot of data and I want to add a new feature in input. The "best" way ...
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205 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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1answer
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Use TSFRESH-library to forecast values

Have some issue with understanding how to use TSFERSH-library (version 0.4.0) to forecast next N-values of particular series. Below my code: ...
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Are there labeled multivariate time series data sets where only a subset/partial number of time series is relevant for each class?

I am looking for a data set of multivariate time series data which contains classes that only require a subset of time series for their identification. Assume a human activity recognition data set ...
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1answer
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Feature selection for time series prediction

I'm working on an LSTM-based stock market forecasting problem and trying to figure out a way to select input variables. When calculating correlation between variables (e.g. Close price of Tesla vs ...
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1answer
14 views

What does all zero mean decrease in accuracy (MDA/permutation importance) signify?

I have a model I've trained on ~3400 features with ~500 samples (40:20:20 train:test:val) that I've calculated MDA on using the eli5 package. However, all the features are zero when I calculate this ...
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Choosing the best set of features when forced to choose M out of N available features

Given: N features that map to some label Y using a Neural Net(NN)- it's a classification problem. Problem: I want to get away by using only a subset of features denoted by M, where M<N. Now I am ...
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1answer
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How to access the data of the column on which some groupby operation has been carried out? [closed]

Suppose there is a pandas dataframe which has one column consisting of names of something, and there are multiple entries respective to each entry in the first column. To count the number of entries ...
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1answer
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In feature selection, I came across a situation where NaN were filled by median of the column values

Why the median value is used for NaN? Why not something else like mean? What is the logic behind using the median value?
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1answer
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Should I scale high ranging ordinal fields?

In the left column, I have an ordinal integer field. In the right column, I have a scaled float feature. Should I scale the ordinal field since it is getting so much bigger than the other feature?
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Feature Importance without Random Forest Feature Importances

Is their an intuitive way of finding feature importances without just using the random forest feature importances method? I have a binary logistic regression problem where I have binary features (1 or ...
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Can features negatively correlated with the target be used?

In feature selection (for a regression problem), can features that are negatively correlated with the target variable be chosen to predict the target? I don't think negative correlation means the ...
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1answer
478 views

Knowing Feature Importance from Sparse Matrix

I was working with a dataset which had a textual column as well as numerical columns, so I used tfidf for textual column and created a sparse matrix, similarly for the numerical features I created a ...
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2answers
933 views

LightGBM - Why Exclusive Feature Bundling (EFB)?

I'm currently studying GBDT and started reading LightGBM's research paper. In section 4. they explain the Exclusive Feature Bundling algorithm, which aims at reducing the number of features by ...
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1answer
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Can I apply feature selection before splitting by requiring selection occurs > 90% of time

I want to move the feature selection step to before splitting to save time and allow bigger input dataset. If, in repeated subsamples, a feature is selected in over X percentage of cases I will keep ...
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1answer
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XGBoost - feature importance just depends on the location of the feature in the data

I'm trying to do some feature selection using XGBoost, but the feature importance chart just spits out the features in order of appearance. The feature that is in the first column in the xtrain data ...
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1answer
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How do feature selection on a sparse matrix?

Say I want to do features selection on a sparse matrix, i.e., 10,000 rows x 1500 features, but the matrix is mostly sparse. Let's say the features are all numeric and the target is binary and discrete....
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Feature selection to improve quadratic discriminant analysis score

I have to solve a multiclass classification problem in python, I'm using scikit-learn. My dataset has got 8000 rows and 21 columns (20 features + 1 class)and my goal is to achieve a certain value of ...
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When should I use StandardScaler and when MinMaxScaler?

I have a feature vector with One-Hot-Encoded features and with continous features. How can I decide now, which data I shall scale with StandardScaler and which data scale with MinMaxScaler? I think I ...
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1answer
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How to do backward features elimination when considering interactions between them

I have a multi linear regression problem, $Y$ is my target and $X_1, X_2, X_3$ are my features. In my regression, I consider the interaction between $X_1, X_2, X_3$ and I add a bias. So my problem ...
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1answer
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comparison of t-SNE and PCA and truncate SVD

How to compare the trucate SVD ,PCA, and T-SNE? What we can say about features if t-SNE and PCA and truncate SVD digaram is in this figure?
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Should feature selection give observable patterns?

I have a dataset of 7 trips on a vehicle, where a component fault occurred on the 4th trip and was fixed following that. The goal is to predict when the fault will occur for similar datasets. The ...
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2answers
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How to perform feature selection on dataset with categorical and numerical features?

I am working on a dataset with 30 columns (29 numerical, 1 non-ordinal categorical). I hot-encoded the categorical feature and reached at 35 columns. To improve training efficiency, I want to perform ...
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1answer
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variance threshold, returning the names of the selected features

I am trying the variance threshold method for the first time and I am following the example in sklearn to work on it. ...
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2answers
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Can I expect necessarily higher accuracy when feature selection/dimension reduction is used to select a subset of features?

The feature selection/dimension reduction is performed to eliminate irrelevant or redundant features so it will improve the computation efficiency (less computationally expensive). My question is that ...
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Literature on selecting specific dimensions in a word embedding vector

I am aware that the different dimensions in the word embedding represents different information and algebraic operations can be performed between two embeddings for example. Can anyone point me to ...
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Data Selection & Visualization Tool

I am looking for a tool that will show neatly all the rows from a large table (100GB+) for complex selection conditions from an sql/text/csv table. DB may be on linux or windows. Looking for easy ...
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2answers
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feature selection in sklearn?

the RFECV takes the estimator and finds which features are important according to that estimator. But, it gets slow when we are dealing with data with many features. But, if we use trees they give us ...
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use genetic algorithm as a feature selection for text classification

how to apply the genetic algorithm as a feature selection for text classification in python I need to use GA to select most relevant feature in text classification
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Feature selection inside Random Forest

I understood random forest is building a model with multiple decision trees, Row sampling is based on bootstraping My question is how feature selection is happening for each tree ? Any help would be ...
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How to deal with different audio formats for audio classification?

I am working on an audio classification problem statement to classify between two audio classes. I have collected samples from jotform, they are providing audio widget to collect .wav audio but it ...
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2answers
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Decision Trees and Feature Selection

I'm trying to experiment with the performance of different machine learning algorithms before and after applying feature selection. I tested SVM, Random Forest, KNN, Linear Regression, and, Decision ...
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1answer
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Determine how each feature contribute to XGBoost Classification

so for a summary of what I have done: My dataset has 5 classes and 10 parameters. I used XGBclassifer from sklearn to investigate if I could use those 10 parameters to predict the class of each data ...
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3answers
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Features selection in KNN

I have a naive question about using the K Nearest Neighbor algorithm: is feature selection more important in KNN than in other algorithms? If a particular feature is not predictive in a neural ...
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1answer
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Feature relevance in PCA + kmeans algorythm

Working on the World Happiness Report dataset, i have N countries with M features and a happiness score. This is the parameter I built 3 classes from: happy, medium, unhappy (numerical intervals of ...
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how to improve score of automl regressor

I was trying to solve a regression problem on HackerEarth. I got to a score of 81.20 using XGBRegressor after some data preprocessing, the top ranker had a score of 81.55. Some one suggested me to use ...
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1answer
577 views

Explanation of how DeepExplainer works to obtain SHAP values in simple terms

I have been using DeepExplainer (DE) to obtain the approximate SHAP values for my MLP model. I am following https://github.com/slundberg/shap and DE's performance is very high in terms of computation ...

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