Questions tagged [principal-component-analysis]

For questions related to principal component analysis (PCA), which is commonly used in machine learning for dimensionality reduction.

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Unable to meet desired mean squared error

I wish to get MSE < 0.5 on test data (https://easyupload.io/zr7xf3) which is 20% of given data chosen randomly. But I am reaching 0.73 using both plain Ridge Regression as well as a neural network ...
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2answers
92 views

The math behind PCA

I am trying to understand the math behind PCA. I can only solve it in the case of mapping vectors to 1 Dimensional space. How to solve the math in the case we reduce the number of dimension is greater ...
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52 views

Looking for the proper algorithm to compress many lowres images of nearby locations

I have an optimization problem that I'm looking for the right algorithm to solve. What I have: A large set of low-res 360 images that were taken on a regular grid within a certain area. each of these ...
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How to deal with large number of features for Anomaly Detection

I am trying to build anomaly detection with low false positives .Dataset that i am using is a patient health sensor data. A number of parameters from the patient's sensors are collected hourly and I ...
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2answers
38 views

Is it theoretically possible (or impossible) that principal component analysis worsens the performance of the model?

In case I had a prediction model and decided to add a PCA step prior to the model, is it theoretically possible/impossible that the number of output dimensions that is better for all tests may perform ...
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29 views

PCA + LDA feature extraction

I am trying to reduce the size of my features vectors using PCA and LDA. Following the approach presented here, I cannot understand step 3 and step 4 described in that approach. Why is the ...
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25 views

Multiple-dimension scaling (MDS) objective for MDS and PCA

The following is the MDS Objective. Let's think of a senario where I apply MDS with/from the solution I obtained from PCA. Then I calculate the objective function on the initial PCA solution and MDS ...
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2answers
65 views

What are examples of approaches to dimensionality reduction of feature vectors?

Given a pre-trained CNN model, I extract feature vector of images in reference and query dataset with several thousands of elements. I would like to apply some augmentation techniques to reduce the ...
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23 views

Human identification using gait analysis

I am working on a human identification by gait analysis project. So far, I have managed to extract the Gait Energy Image(GEI) of a silhouette. I am stuck on finding a way to move forward with my ...
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31 views

What is the difference between principal component analysis and singular value decomposition in image processing?

What is the difference between principal component analysis and singular value decomposition in image processing? Which one performs better, and why?
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35 views

Do the eigenvectors represent the original features?

I've got a test dataset with 4 features and the PCA produces a set of 4 eigenvectors, e.g., ...