Questions tagged [features]

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25 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 ...
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2answers
41 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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1answer
17 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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1answer
8 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 ...
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0answers
36 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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1answer
23 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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1answer
81 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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0answers
19 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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1answer
23 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 ...
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0answers
17 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 ...
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0answers
19 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, ...
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0answers
50 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. ...
2
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1answer
676 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 ...
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1answer
36 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
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2answers
37 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 ...
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0answers
30 views

Transform skewed ratio data (value range from 0 to 1) to reduce the skew

I want data clusters. Because my cluster algorithm doesn't work with skewed data I want to change that in advance. I have ratio data, i mean probabilities (values between 0 and 1). But these data are ...
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2answers
32 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 ...
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2answers
113 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 ...
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1answer
24 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 ...
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2answers
68 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?
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0answers
95 views

How to use additional variables that are not available in test set?

I have additional variables in my dataset that are somewhat correlated to the continuous target variable, but that are completely unavailable in the test set. So, I'm wondering how the best to use ...
4
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2answers
247 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? ...
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1answer
20 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, ...
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0answers
18 views

Feature Analysis to Maximize Classification

I keep coming across a pattern in problems I need to solve.  Perhaps one of you might have a suggestion on the best method to solve this one: Assume 3 features, X1, X2, X3.   X1, X2 are real valued ...
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2answers
50 views

Interpretation of PCA visualisation

I am trying to build a classifier to predict the ratings of a show during a specific time. I have extracted around 109 features, some relating to the time field namely, Day of Year Month of year ...
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2answers
405 views

Finding Feature Importance in CNN's?

Let's say I have images of cars. For each image in the dataset, I have let's say 3 pictures of the same car but in different angles. 1) The first image is the picture of the car from the front. 2) ...
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0answers
23 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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0answers
11 views

How to do feature engineering on this situation that the almost all label of high count part is 1

I get a feature-target analysis as follows: ...
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0answers
21 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 ...
1
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1answer
24 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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0answers
70 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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2answers
172 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 ...
2
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2answers
2k 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
22 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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0answers
30 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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0answers
17 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 ...
0
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1answer
62 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 ...
2
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1answer
41 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
40 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 ...
0
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1answer
63 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: ...
1
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2answers
97 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 ...
1
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1answer
417 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 ...
0
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4answers
332 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 ...